No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Sustainable Pavement Management
Abstract
Insufficient investment in the public sector together with inefficient maintenance infrastructure programs lead to high economic costs in the long term. Thus, infrastructure managers need practical tools to maximize the Long-Term Effectiveness (LTE) of maintenance programs. This paper describes an optimization tool based on a hybrid Greedy Randomized Adaptive Search Procedure (GRASP) considering Threshold Accepting (TA) with relaxed constraints. This tool facilitates the design of optimal maintenance programs subject to budgetary and technical restrictions, exploring the effect of different budgetary scenarios on the overall network condition. The optimization tool is applied to a case study demonstrating its efficiency to analyze real data. Optimized maintenance programs are shown to yield LTE 40% higher than the traditional programs based on a reactive strategy. To extend the results obtained in this case study, a set of simulated scenarios, based on the range of values found in the real example, are also optimized. This analysis concludes that this optimization algorithm enhances the allocation of maintenance funds over the one obtained under a traditional reactive strategy. The sensitivity analysis of a range of budgetary scenarios indicates that the funding level in the early years is a driving factor of the LTE of optimal maintenance programs.
... CONTACT Khaled A. Abaza kabaza@birzeit.edu In particular, the pavement management system (PMS) has been proposed as a comprehensive mathematical tool to assist in solving the pavement management problem at the network level (Khattak et al., 2008;Li et al., 2006;Sebaaly et al., 1996;Torres-Machí et al., 2015). The pavement management problem is essentially an optimisation problem recognised to be complex to solve because of the need to consider a huge number of pavement sections, a large number of potential maintenance and rehabilitation strategies, while forecasting a number of years within a study period typically extending up to ten years. ...
... Several pavement management models have been developed in the last three decades but very few gained international publicity. This is because the majority are found either too unreliable or too complex to use and labelled 'data hungry' as they require extensive data records (Khattak et al., 2008;Li et al., 2006;Sebaaly et al., 1996;Torres-Machí et al., 2015). Generally, there are three key requirements for the successful implementation of any PMS. ...
A simplified pavement management model for developing a long-term rehabilitation schedule is proposed for flexible pavement. The model deploys the discrete-time Markov model to predict the deterioration of both original and rehabilitated pavement performances. The main objective of the proposed model is to generate optimal annual rehabilitation cycles over a specified analysis period. This objective is achieved by optimizing a cost-effectiveness index defined as the ratio of anticipated performance improvement and annual rehabilitation cost. It therefore seeks to find the optimal annual rehabilitation cycle that maximizes pavement condition improvement and minimizes rehabilitation cost. The corresponding optimum model is subject to a number of constraints that include the non-negativity constraints, upper-limit variable value constraints, and budget constraints. However, the rehabilitation variables are incorporated into the state probabilities rather than the transition matrix when predicting future deterioration of rehabilitated pavement. The optimum model can simply be solved using an exhaustive search approach as it makes use of a limited number of rehabilitation variables. Two case studies are presented to demonstrate the potential uses of the proposed model. The first one examined the relationship between variable budget levels and sustainable long-term pavement performances, whereas the second one investigated the long-term cost-effectiveness of individual rehabilitation treatments. Generally, the sample results re-emphasized the famous theme of “better roads at lower costs”.
... Multicriteria decision making (MCDM) methods have already been used in the pavement field to integrate different criteria in the decision-making process (Wu et al. 2012;Torres-Machi et al. 2015). Previous studies have used approaches such as the multiattribute approach (Giustozzi et al. 2012;Bryce et al. 2014) and the analytic hierarchy process (AHP) (Smith and Tighe 2006;Farhan and Fwa 2011;Gurganus and Gharaibeh 2012;Oswald and Treat 2015;Inti and Tandon 2017). ...
... AHP helps the decision maker to intuitively solve a complex choosing problem that may involve environmental, social, economic, and technical factors. AHP shows strengths (such as the calculation of consistency ratio to assure decision makers and its ability to incorporate both qualitative and quantitative criteria) and limitations (such as the complex and time-consuming implementation and computation when increasing the number of criteria considered in the evaluation) (Whitaker 2007;Saaty et al. 2009;Kabir et al. 2014;Torres-Machi et al. 2015). AHP has been selected in this study not because of the strengths of the method, but because it is extensively used in infrastructure management. ...
This paper presents findings of a recent study that was conducted in Canada on the quantification of pavement sustainability. The ultimate goal of this study was to develop a framework and explore the use of multicriteria decision-making techniques to formally assess the sustainability of pavement engineering alternatives. While sustainability is of increasing concern in pavement engineering, environmental performance is rarely used by pavement managers to select maintenance practices. There is therefore a need to develop a framework for the practical consideration of environmental effects in pavement management. This paper aims to provide a better understanding on the use of multicriteria decision-making techniques based on hierarchy process (AHP) and choosing by advantages (CBA) for the integration of sustainable aspects in the decision-making process of pavement management. A case study comparing pavement maintenance technologies using cold-in-place recycling and traditional solutions based on mill and overlay is analyzed for illustrative purposes. Results obtained using both multicriteria techniques are compared, including a sensitivity analysis on the importance of sustainability criteria in the evaluation of maintenance alternatives. Results obtained from this case study show that AHP and CBA provide consistent recommendations in which cold-in-place technologies are preferred over traditional alternatives. However, CBA presents the advantage of separating cost from the analysis, letting the agency to decide whether they are willing to pay more to use more sustainable alternatives. This finding has significant implications for engineering practice, given that AHP is widely used not only in the pavement field but in infrastructure management. Further research is needed to incorporate social aspects and existing barriers for the implementation of sustainable technologies in the proposed sustainability evaluation.
... (v) Transport Infrastructure. 7.2% of the manuscripts deal with the sustainability of different elements and topics related to transport systems, such as the sustainable design of road pavements [87][88][89][90], the selection of the optimal road location [91], or the development of assessment tools for the evaluation of transport projects [92]. (vi) Others. ...
... In the field of building design, Mosalam et al. [22] consider a discount rate of 3%, Jalei et al. [25] assume a discount rate of 5%, and Perini and Rosasco [24] evaluate three different economic scenarios, with discount rates that range from 4.5% to 5.5%. Torres-Machí et al. [89], when assessing the sustainability of road pavement treatments, assume a discount rate of 5%. Klein and Whalley [68] evaluate a cost discounting range that varies from 3% up to 10%. ...
Given the great impacts associated with the construction and maintenance of infrastructures in both the environmental, the economic and the social dimensions, a sustainable approach to their design appears essential to ease the fulfilment of the Sustainable Development Goals set by the United Nations. Multicriteria decision-making methods are usually applied to address the complex and often conflicting criteria that characterise sustainability. The present study aims to review the current state of the art regarding the application of such techniques in the sustainability assessment of infrastructures, analysing as well the sustainability impacts and criteria included in the assessments. The Analytic Hierarchy Process is the most frequently used weighting technique. Simple Additive Weighting has turned out to be the most applied decision-making method to assess the weighted criteria. Although a life cycle assessment approach is recurrently used to evaluate sustainability, standardised concepts, such as cost discounting, or presentation of the assumed functional unit or system boundaries, as required by ISO 14040, are still only marginally used. Additionally, a need for further research in the inclusion of fuzziness in the handling of linguistic variables is identified.
... Life Cycle Cost Analysis (LCCA) is used in asset management to evaluate different maintenance and rehabilitation strategies. In addition to maintenance and rehabilitation costs, agencies started to include other factors such as salvage value and user costs and environmental costs in the LCCA (Bryce et al. 2014;Mallela et al. 2011;Ozbay et al. 2004;Smith and Fung 2006;TAC 2013;Torres-Machí et al. 2015). However, to date, the impact of asset value on LCCA is not considered. ...
... As noted, the LCCA is used in asset management to evaluate different maintenance and rehabilitation strategies. In addition to maintenance and rehabilitation costs, agencies started to include other factors such as salvage value and user costs and environmental costs in the LCCA (Bryce et al. 2014;Mallela et al. 2011;Ozbay et al. 2004;Smith and Fung 2006;TAC 2013;Torres-Machí et al. 2015). However, to date, the impact of asset value on LCCA is not considered. ...
... However, FHWA [4] pointed out that there should be a striking balance between particular importance and feasibility. Therefore, it is necessary to perform a multi-criteria pavement analysis before adopting any noise abatement techniques [73][74][75]. Multi-criteria analysis includes number of factors such as technical feasibility, the unique characteristics of highway generated noise, cost, overall public interest, and aesthetic considerations that should be taken into account before choosing a noise abatement technique [4]. In addition, it is also critical to incorporate sustainability approach in adopting any noise abatement technique so that it is economically viable and environmentally sustainable [74,76]. ...
... Multi-criteria analysis includes number of factors such as technical feasibility, the unique characteristics of highway generated noise, cost, overall public interest, and aesthetic considerations that should be taken into account before choosing a noise abatement technique [4]. In addition, it is also critical to incorporate sustainability approach in adopting any noise abatement technique so that it is economically viable and environmentally sustainable [74,76]. This section summarizes common traffic noise abatement procedures. ...
Noise pollution due to highway traffic has drawn the attention of transportation agencies worldwide. Noise pollution is an irritant to residents, especially in urban areas near roads with high traffic volume. In addition to its adverse effects on the quality of life, traffic noise can induce stress that could lead to sleep disturbance and anxiety. Traditionally, noise barrier walls have been used for highways to mitigate traffic noise. However, using barrier walls as a noise abatement measure has proven to be very expensive. In addition to the cost, noise barrier walls are not always effective because they must break the line of sight to work properly, which is not always possible in case of intersections or driveways. Therefore, researchers especially from Europe and USA have been very proactive to reduce the noise at source. A number of research studies show traffic noise can be reduced by using an alternative surface type or changing texture of the pavement while complying with other requirements of sustainability, i.e., safety, structural durability, construction and maintenance costs. This paper presents a comprehensive review of the research conducted on this subject. A review of the tire-pavement noise generation and amplification mechanism, various traffic noise measurement methods and correlation among these methods, in addition to the abatement techniques used by various agencies to reduce pavement noise, is also presented.
... The addressing of this issue has been traditionally handled through the development of lifecycle analysis procedures (Abaza 2017;Heravi and Esmaeeli 2013;Hong and Prozzi 2015;Santos and Ferreira 2013;Suwarto, Parry, and Airey 2023). A pavement management system (PMS) is traditionally applied at the network-level to generate a long-term pavement maintenance and rehabilitation (M&R) schedule (Saha and Ksaibati 2016;Torres-Machí et al. 2015). The M&R schedule typically consists of project candidate lists with preliminary M&R treatments. ...
The life-cycle duration (TLC) is typically assumed constant in pavement life-cycle analysis. The added scientific value of this paper is that (TLC) is considered a variable parameter to be estimated from the performance curve using a variable terminal condition rating. A variable (TLC) requires using the equivalent annual value (EAV) instead of the net present value for cost estimation. The life-cycle performance (LCP) curve is constructed using two routine maintenance cycles separated by one major rehabilitation action. The time parameters associated with LCP curve are estimated from the inverse performance function based on the initial, present and terminal condition ratings. The equivalent annual cost and performance associated with a particular LCP curve are used to compute cost/performance (C/P) ratio for optimal maintenance and rehabilitation (M&R) plan selection. The EAV represents the costs of two routine maintenance cycles and one major rehabilitation action. Sample results obtained from three case studies have indicated the reliability of the proposed LCA approach in yielding optimal M&R plans. At the project-level, the optimal M&R plan associated with 7 m/km terminal IRI value resulted in (0.949) minimal (C/P) value. However, the optimal M&R plan with 3.25 terminal PSI yielded (1.50) minimal (C/P) value.
... The periodic intervention typically includes major rehabilitation actions such as plain overlay, cold milling and overlay, and reconstruction, which can restore the pavement's structural integrity. Because huge financial resources are required to maintain and restore the pavement network, a mathematical tool called pavement management system (PMS) has emerged to assist decision-makers in obtaining the optimal maintenance and rehabilitation (M&R) plan that can maximize pavement conditions subject to budget limitations (Mandiartha et al., 2017;Sebaaly et al., 1996;Li et al., 2006;Torres-Mach ı et al., 2015;Kim et al., 2018;Hafez et al., 2021). ...
This paper proposes three different models for investigating the long-term performance of routine maintenance works using the discrete-time Markov model. The three models are called (M1, M2, and M3), which represent specific forms of the transition probability matrix. The (M1) model only incorporates the routine maintenance variables (Mi,i-1) under the assumption of only one-state upgrade. The (M2 and M3) models incorporate both routine maintenance variables (Mi,i-1), and major rehabilitation variables (Qi,1) under the assumption of upgrade to condition state (1). Two different modeling methods are proposed for pavement long-term performance prediction in the presence of maintenance and rehabilitation (M&R) variables. The first one is the project-level approach as applied to small pavement networks which assumes that all M&R works can be performed in a short-time period. The second one is the network-level approach which requires the M&R works to be spanned over the entire year as applied to large pavement networks. A model cost-effectiveness index is proposed to evaluate the long-term performance of potential M&R schedules under an unconstrained annual budget. In contrast, M&R variable cost-effectiveness indices are proposed as useful parameters for yielding optimal M&R schedules under a constrained annual budget. The sample results indicated the unrealistic performance of the (M1) model and the usefulness of the (M2 and M3) models in yielding reliable long-term M&R schedules.
... This is because resurfacing is generally a low-cost maintenance treatment compared to other options, and frequent resurfacing prevents roads from further deterioration. Previous studies [53,54] also have found similar priority rankings for road maintenance. Due to the differences in maintenance costs, road asset managers prefer to attend low-cost early-stage maintenance activities rather than waiting for expensive rehabilitation activities at a later stage [36,55,56]. ...
Roads and water pipe assets undergo various deterioration processes due to the high demand for their services. Maintenance of these assets is often planned as individual assets, and the interdependency among different assets is neglected. An integrated framework for cross-asset maintenance is required for optimum utilization of the available funds for asset maintenance. To date, there are very few studies focusing on the use of the analytical hierarchy process (AHP) for cross-asset maintenance of roads and water pipe assets. Therefore, this research aims to develop an integrated fund allocation model for the maintenance of road and water pipe assets. A model was developed using AHP analysis based on expert opinions captured through a questionnaire in order to obtain optimum maintenance fund allocation for the cross-assets, roads, and water pipes. Then, a case study corridor segment with the considered cross-assets was selected, and a trade-off analysis was conducted for the intervention alternatives considering different levels of service (LOS) of the asset elements. The results of the trade-off analysis can be used to identify the optimum intervention alternative that satisfies the budget requirement and results in the maximum benefit. Overall, asset managers can use the approach presented in the present study to develop a cross-asset fund allocation model when multiple assets are involved in maintenance. Doi: 10.28991/CEJ-2024-010-02-01 Full Text: PDF
... Maintenance is crucial to enhance the service life of pavements [1]. In recent years, chip seal has emerged as an economic and environmentally friendly maintenance strategy and has been applied on numerous roads [2]. This technique involves the application of asphalt cement or emulsions on the original road surface, followed by the placement of cover aggregates or chips. ...
The use of asphalt emulsion chip seal and hot rubber chip seal as pavement preservation techniques has been gaining popularity. This study aims to compare the laboratory performance of asphalt emulsion and hot rubber asphalt used in chip seal applications. Interlayer shear strength (ISS) and interlayer tensile strength (ITS) tests were designed to evaluate the bond quality of the chip seal samples prepared for both materials. The sweep test was used to estimate the aggregate loss of the chip seal on the asphalt pavement. The universal testing machines were used to evaluate the deterioration of the ISS and ITS values under cyclic load conditions, while the tensile and shear bond properties of chip seals under wet-freeze conditions were evaluated using freeze-thaw cycles. Results showed while both materials experienced a decline in their ISS and ITS values following repeated cycles of load and freeze-thaw, the hot rubber chip seal demonstrated significantly higher ISS and ITS values than the asphalt emulsion chip seal (48–111% and 36–102%, respectively). Moreover, the hot rubber chip seal exhibited better performance in terms of aggregate retention and cohesive strength. The aggregate gradation would affect the aggregate retention and cohesive strength. Nonetheless, both treatments are deemed acceptable for pavement maintenance. The weak bond between hot rubber asphalt or asphalt emulsion and aggregate could be attributed to cyclic load and freeze-thaw conditions.
... A detailed literature survey was conducted on various maintenance techniques widely used in the field of pavement maintenance so that a proper scientific assessment of maintenance can be done for the pavements of Himalayan region. Various literatures were studied to determine the unit cost and service life of main pavement maintenance techniques used in rural hill roads [4,18,[23][24][25][26][27][28]. Average per-unit cost of each technique differs depending on the project's location, quantity of materials used, availability of local raw materials, and weather conditions. ...
Maintenance planning of low volume rural road network is a challenging task due to its large length and importance to the concerned habitation. The proposed methodology is focused on developing a cost-effective maintenance plan for low volume rural Himalayan hill roads by considering the predominant distresses and factors. Maximizing overall network pavement condition rating while minimizing the budget is taken as the objective function in the optimization problem. The maintenance plan is optimized using Knapsack modified Genetic Algorithm technique developed in MATLAB. Validation of the proposed model was done by applying it to a case study of 42 low volume rural hill roads of Hamirpur district of Himachal Pradesh state in India, located in the Himalayan region. Knapsack modified GA makes maintenance planning easier by considering different scenarios of budgetary limitations varying from 0 to 100% of total need. The present model can be very helpful for pavement maintenance planners in developing an optimized cost-effective maintenance program in developing countries where budget limitation is a big concern.
... From Eqs. (2) and (5), we can find that they are established for the TO of a single member and that loads are generally imposed in the tests. However, many influencing parameters may be involved in the practical TO design of bridges (Torres-Machí et al., 2015;Cid Montoya et al., 2018). Thus, the research object in this paper is regarded as the statically indeterminate structural design. ...
To reduce the pollution emissions of bridges to the environment, researchers need to conduct more in-depth research and design the structure. Today's architectural, structural, and mechanical engineers pay more attention to funders' requirements and pursue the maximization of economic benefits. The research begins with establishing a theoretical model of the bridge's robustness under dead and dynamic loads: applying a Three-Dimensional (3D) solid finite element model, swarm intelligence optimization algorithm, and mathematical model of quadratic interpolation approximation solves the problems of multiple loads, discrete data, and convergence. Based on the establishment and analysis data of the research model, the research, and analysis of the optimal topology bridge model are completed, and the optimal structure size is obtained. The carbon emissions from the bridge optimization decreased by 2242.92 t, accounting for 25% of the total emissions. This data is shocking, and it also gives investors and governments a painful reminder that they must pay more attention to the sustainable construction and development of the construction industry and achieve the goal of zero carbon emissions in the construction industry as soon as possible.
... La construcción se encuentra a nivel mundial entre las principales actividades de estrés ambiental y económico que comprometen nuestra sociedad, siendo la industria del cemento la que genera uno los mayores impactos [1]. Si bien la optimización de materiales en el diseño de las infraestructuras ha sido objeto de estudio en los últimos años [2][3][4], el ODS-9 supone la necesidad de incorporar en los diseños futuros conceptos complejos como la sostenibilidad o la economía circular [5] para poder alcanzar las metas propuestas para 2030. 1 Neutrosophic logic applied to the multi-criteria evaluation of sustainable alternatives for earth-retaining walls. Sixth International Conference on Mechanical Models in Structural Engineering Valladolid (Spain). 1 -3 Dec 2021. ...
El diseño sostenible de las infraestructuras es uno de los aspectos clave para la consecución de los Objetivos de Desarrollo Sostenible, dada la reconocida magnitud de los impactos tanto económicos como ambientales propios del sector de la construcción. Las metodologías de decisión multicriterio permiten abordar el diseño sostenible de las infraestructuras, considerando simultáneamente la repercusión de un diseño en las distintas dimensiones de la sostenibilidad. El presente artículo propone el uso de la lógica neutrosófica para resolver uno de los principales problemas asociados con la toma de decisiones: la subjetividad de los expertos involucrados. Mediante el enfoque neutrosófico de la metodología multicriterio AHP (del inglés, Analytic Hierarchy Process) y el uso de la técnica VIKOR (del serbio, VIseKriterijumska Optimizacija I Kompromisno Resenje), se analizan los impactos económicos y ambientales asociados a cuatro diseños de muros de contención. En el presente análisis, la respuesta más sostenible a lo largo de su ciclo de vida ha resultado ser la del muro de gaviones.
... Ayrıca, çatlaklar bakıma alınmazsa trafik yoğunluğunun artmasına, kaplamanın eskimesine ve zamanla diğer yapılardan bağlarını ayırarak (debonding) yol bakım maliyetlerini artmasına yol açabilir. Bununla ilgili olarak, dünya çapında, kaplama inşası ve bakımı için her yıl 400 milyar $ harcanmaktadır [2]. Bu bağlamda, yaygın olarak kaplama çatlaklarının tespiti için geleneksel yöntemlerden olan görsel tabanlı manuel inceleme kullanılmaktadır [3]. ...
Asphalt cracks on the highway surface are one of the most common pavement damage. If these cracks are not detected and taken care of on time, they grow and reach dimensions that will increase traffic safety and density. Therefore, it is very important to carry out the detection of asphalt cracks quickly. Traditional manual crack detection is extremely time consuming, very costly and requires a lot of effort. Therefore, the researchers concentrated their focus on the detection of automatic asphalt cracks. However, although automatic crack detection has been extensively investigated in recent years, it is still a difficult task due to the fact that cracks have different densities and the complexity of the pavement environment. In this study, a convolutional neural network-based method is proposed to overcome this difficulty. The proposed method was developed based on the convolution and inverted residual block structures used by MobileNetv2, which is known for its success and lightweight in classification and segmentation. As a result of the experimental tests, it is seen that the performance of the proposed method is higher than the other methods in the literature. This means that automatic asphalt crack detection is more successful.
... As a result, research has been conducted in recent times in the assessment of infrastructures focusing on their economic, environmental, and social impacts. Although interest has arisen on the sustainability assessment of a wide variety of infrastructure types, such as pavements [2,3], buildings [4][5][6], earth retaining walls [7][8][9], railway tracks [10], dams [11], and others, much consideration has always been given to the sustainable design of bridges in particular. ...
Since establishing the Sustainable Development Goals in 2015, the assessment of the sustainability performance of existing and future infrastructures has been in the spotlight of the scientific community. This is because the construction sector is essential for promoting the social welfare and economic development of countries, but is also one of the main environmental stressors existing to date. However, assessing infrastructure sustainability throughout its life cycle remains a significant challenge, as the criteria involved in sustainable design are often complex and conflicting. The Analytic Network Process (ANP) is recognized as a powerful decision-making tool to model such problems. Here, the life cycle sustainability performance of different design alternatives for a concrete bridge near the shore is evaluated using ANP. The obtained results are compared with those obtained using the conventional Analytical Hierarchy Process (AHP). The results obtained using ANP are more reliable than those derived from the conventional AHP in terms of the expert’s consistency and the number of comparisons made.
... However, there has been an exponential increase in research on the construction sector oriented toward a sustainable approach and the search for a circular economy in the last decade. Lately, several studies have been carried out to evaluate sustainability in construction projects, from bridges [4,5], buildings [6,7], construction elements such as pavements [8], or retaining walls [9,10], among many other aspects of construction design and management. ...
The analytic network process (ANP) is a discrete multi-criteria decision-making (MCDM) method conceived as a generalization of the traditional analytic hierarchical process (AHP) to address its limitations. ANP allows the incorporation of interdependence and feedback relationships between the criteria and alternatives that make up the system. This implies much more complexity and intervention time, which reduces the expert's ability to make accurate and consistent judgments. The present paper takes advantage of the usefulness of this methodology by formulating the model for exclusively quantitative variables, simplifying the decision problem by resulting in fewer paired comparisons. Seven sustainability-related criteria are used to determine, among four design alternatives for a building structure, which is the most sustainable over its life cycle. The results reveal that the number of questions required by the conventional AHP is reduced by 92%. The weights obtained between the AHP and ANP groups show significant variations of up to 71% in the relative standard deviation of some criteria. This sensitivity to subjectivity has been implemented by combining the ANP-ELECTRE IS methods, allowing the expert to reflect the view of the decision problem with greater flexibility and accuracy. The sensitivity of the results on different methods has been analyzed.
... When several alternatives and multiple criteria need to be considered, using multicriteria decision-making methods (MCDM) is essential. They may be applied to different fields [53][54][55], allowing the decision maker to assess intricate problems involving complex problems involving multiple and conflicting criteria based on the subjective opinions of a group of experts or interested parties [56]. ...
Considering the importance of the development of new housing projects, the purpose of
this research is to provide a model oriented to the identification of the most sustainable alternative in single-family housing projects of social interest from the perspective of life cycle thinking (LCT) and the analytical hierarchical process (AHP). A ceramic masonry project and a concrete masonry project were evaluated. In the environmental dimension, the results showed that the ceramic masonry project had more significant environmental impacts and greater damage to human health and the availability of resources and ecosystems. In the social dimension, it was found that there are discrepancies between the salaries in the construction supply chain and that the concrete masonry project had
better social characteristics than the ceramic masonry project. The economic dimension revealed that the concrete masonry project was more attractive. Relating the environmental, social, and economic dimensions’ results, through the combination of LCT and AHP, it was found that the concrete masonry project presented a combination of more sustainable characteristics than the ceramic masonry project in the majority of the results. Among the implications of the study carried out here is the advancement
of sustainability applied to the construction sector.
... The annual budget is 12.2 million dollars. The M&R activities are shown in Table 1 [4][5][6][7][8][9]. ...
Choosing an appropriate strategy in order to maintain pavements has become a significant concern. Recently, pavement agencies tackle large-scale networks, which makes the problem complicated. To prevail in this complexity, utilizing metaheuristic algorithms can be an ideal approach. By increasing the dimension of the problem, the competency of metaheuristic algorithms is by far enhanced. To this end, the water cycle algorithm is applied to solve the problem. In this investigation, two models, including single objective optimization and multi-objective optimization, are taken into consideration. In the single-objective model, the minimization of the network International Roughness Index (IRI) is considered as the objective function. In multi-objective optimization modeling, minimization of the network International Roughness Index and embodied CO2 emission are taken into account simultaneously. Furthermore, a new constraint is considered in the model, which leads to restricting the budget fluctuation in different years of the analysis period. A network, including 79 segments, is the case study of this investigation. The results reveal that the water cycle algorithm is highly qualified to solve the pavement maintenance and rehabilitation problem. According to results, multi-objective optimization reduces the CO2 emission by 47.2% compared with single-objective modelling. Furthermore, the variation of minimum and maximum cost is less than 20% in the planning horizon.
... Especially in the last five years, there has been an exponential increase in the application of MCDM methods to practically all aspects of the construction sector (Zhu et al., 2021. Some of these MCDM tools above have been used in the sustainable assessment of infrastructure planning (Salas and Yepes, 2020), infrastructures such as bridges (García-Segura et al., 2018;Navarro et al., 2020), building structures (Sánchez-Garrido et al., 2022), constructive elements (Pons et al., 2021) or the management of materials such as pavement composites (Torres-Machí et al., 2015), among others. Other novel methods have been used in fuzzy environments to ensure sustainable prevention of occupational accidents in construction companies (Turskis et al., 2019). ...
The soil is not always suitable or competent to support a direct shallow foundation in construction. In many cases, to avoid costly deep foundations, it is indicated to replace, improve, or reinforce such soil. This paper focuses on evaluating the contribution to sustainability between different soil improvement techniques and the outcome of their application to the foundation of a single-family house as an alternative to the one built. The life-cycle performance in sustainability is compared between the baseline design (without intervention), backfilling and soil compaction, soil-cement columns, rigid inclusion of micropiles, and nailing of precast joists. To characterize sustainability, a set of 37 indicators is proposed that integrate the economic or environmental aspects of each design alternative and its social impacts. A sustainability ranking is obtained for the different alternatives based on the ELECTRE IS method for multi-criteria decision-making (MCDM). The sensitivity of the obtained results is evaluated against different MCDM methods (TOPSIS, COPRAS) and different criteria weights. The evaluation provides a cross-cutting view, comparing the ability and reliability of each technique to prioritize the ground consolidation solution that best contributes to the sustainability in the design of a building's substructure.
... Relevant research mainly focuses on the identification of sustainable performance index and the implementation of sustainability assessment. Sustainability in the construction industry can be treated as the reconciliation of economic, environmental, and social dimensions (Torres-Machí et al., 2015). How to identify and balance the factors for each dimension becomes a major issue for decision makers (Cadena & Magro, 2015). ...
Decision making is a key to business or project success in any sectors, especially in construction that requires handling numerous information and knowledge. Multiple criteria decision making (MCDM) is an important tool for decision problem solving due to simultaneous consideration of multiple criteria and objectives. Various MCDM methods are continually emerging and tend to be increasingly adopted to address the real-world construction problems. Therefore, it is urged to systematically review the existing body of literature to demonstrate the evolution of the mainstream MCDM methods in general and their application status in construction. A total of 530 construction articles published from 2000 to 2019 are selected in this study and then categorized into seven major application areas using a novel systematic literature review (SLR) methodology. The bibliometric analysis is then used to describe the research trend. Subsequently, the qualitative discussion by themes is conducted to analyze the application of MCDM methods in construction. A further discussion makes it possible to identify the potential challenges (e.g. applicability, robustness, postpone effect, dynamic and prospective challenges and scale problem) to existing research. It also contributes to the recommendation of future directions for the development of MCDM methods that would benefit construction research and practice.
... The preventive maintenance technology of asphalt pavement is developing with the development of asphalt concrete technology [1,2]. At present, the main conservation measures include crack sealing, fog sealing, chip sealing, slurry sealing, milling, and resurfacing, local regeneration, reconstruction, and so on [3][4][5][6]. ...
Herein, the effects of the contents of emulsified asphalt, waterborne epoxy resin emulsion, and curing agent on the permeability, bond shear strength, water stability, and aging resistance of epoxy-emulsified asphalt were studied. A formulation of epoxy-emulsified asphalt as a fog-sealing adhesive material was recommended, and a comparison between the fabricated adhesive material and a traditional Chinese fog-sealing adhesive material was conducted to verify the technical performance of the new material. In addition, the strength formation mechanism of the epoxy-emulsified asphalt was revealed via microcosmic analysis. Results show that the curing agent content mainly affects the permeability of epoxy-emulsified asphalt, and the emulsified asphalt content significantly affects the bond shear strength, water stability, and aging resistance. Moreover, the ratio of waterborne epoxy resin emulsion to the curing agent (epoxy ratio) has a certain effect on the bond shear strength. In the recommended formulation (a high-permeability and high-bonding fog-sealing adhesive material, which can be referred to simply as HPBFA), emulsified asphalt accounts for 80% of the total mass of the mixture, and the epoxy ratio is 2:1–3:1. It can improve air permeability, bond shear strength, water stability and aging resistance. The HPBFA-cured material exhibits a continuous three-dimensional network structure, hydrophobic surface, and large contact angle. Furthermore, the initial thermal weight loss temperature of the HPBFA-cured material is significantly higher than the environmental aging temperature. Additionally, the maximum temperature decomposition range is 0–160 °C, indicating improved strength, wear resistance, permeability, and aging resistance of the material.
... The pavement deterioration problem worsens with insufficient maintenance budgets. Globally, every year more than $400 billion is spent on pavement construction and maintenance costs; thus, reducing the inspection-related expenditures and maintenance costs is the primary goal of researchers working in this field (10,11). Early detection of cracks can prevent potential damage and failure (12). ...
Cracks considerably reduce the life span of pavement surfaces. Currently, there is a need for the development of robust automated distress evaluation systems that comprise a low-cost crack detection method for performing fast and cost-effective roadway health monitoring practices. Most of the current methods are costly and have labor-intensive learning processes, so they are not suitable for small local-level projects with limited resources or are only usable for specific pavement types.
This paper proposes a new method that uses an improved version of the weighted neighborhood pixels segmentation algorithm to detect cracks in 2-D pavement images. This method uses the Gaussian cumulative density function as the adaptive threshold to overcome the drawback of fixed thresholds in noisy environments. The proposed algorithm was tested on 300 images containing a wide range of noise representative of different noise conditions. This method proved to be time and cost-efficient as it took less than 3.15 seconds per 320 × 480 pixels image for a Xeon (R) 3.70 GHz CPU processor to determine the detection results. This makes the model a perfect choice for county-level pavement maintenance projects requiring cost-effective pavement crack detection systems. The validation results were promising for the detection of low to severe-level cracks (Accuracy = 97.3%, Precision = 79.21%, Recall= 89.18% and F1 score = 83.9%).
... Pavement management systems have been applied to roads since the 1970s to improve the maintenance of transport infrastructures, but a new impulse focused on sustainable pavement management has emerged, paying special attention to the trade-off between costs, environmental impacts, and social consequences of the investments in road networks [5][6][7]. In this new framework, infrastructure managers must consider a sustainable approach to the management of pavement maintenance to ensure technically appropriate solutions that are economically viable, environmentally sustainable, and socially acceptable, which requires complex solutions to encompass all these principles [8,9]. ...
The use of self-healing asphalt is a good option to extend the lifetime of roads and to improve the sustainability of pavement management systems. A bibliometric analysis based on the Scopus database was carried out to review the global research related to self-healing asphalt from 2003 to 2018 and to identify relevant quantitative characteristics from the research in this period. The results from this analysis revealed that the number of accumulated publications followed an exponential growth, which confirmed the relevance that this research topic has gained during the last years. The study revealed that China was the most productive country, followed by the Netherlands, where the most prolific institution is located: Delft University of Technology. Some important research features of the two main approaches most frequently used to develop asphalt mixtures with enhanced self-healing abilities (external heating and encapsulated rejuvenating agents) are compiled in this work.
... The unit cost of treatment application is extracted from RMTO. The treatments unit CO 2 emission is extracted from authentic international publications (Chehovits and Galehouse 2010, Giustozzi et al. 2012, Torres-Machí et al. 2015. The values presented in Table 5 are applied in the optimisation modelling to obtain the optimal M&R planning. ...
CO2 emission reduction in large-scale pavement network maintenance planning has been an immense concern. The conventional single-objective optimisation modelsoverlook environmental issues such as CO2 emission. However, the introduced multi-objective optimisation aims to enhance the network condition and minimise CO2 emissions simultaneously. Two single-objective (coyote optimisation algorithm and genetic algorithm) and two multi-objective metaheuristic algorithms (multi-objective coyote optimisation algorithm and non-dominated sorting genetic algorithm) are employed to assess the effectiveness of the introduced environmental approach. Pavement maintenance planning optimisation requires the deterioration function formula and treatment improvement equation to be modelled. Hence, a new machine learning method called ‘differential evolutionary programming’ is introduced, which can provide the output-input formula. Differential evolutionary programming predicts the pavement deterioration value and overlay improvement with R² of 0.992 and 0.970, respectively. The results indicate that the coyote optimisation algorithm’s objective function is 66% lower than that of the genetic algorithm. Likewise, the multi-objective coyote optimisation algorithm reduces the first objective function by 72% on average compared to the non-dominated sorting genetic algorithm. The grey relational analysis is performed to compare single-objective and multi-objective optimal solutions. All optimal solutions presented by multi-objective modelling dominates the single-objective optimisation optimal solution based on the grey relational grade.
... The pavement deterioration problem worsens with insufficient maintenance budgets. Globally, every year more than $400 billion is spent on pavement construction and maintenance costs; thus, reducing the inspection-related expenditures and maintenance costs is the primary goal of researchers working in this field (10,11). Early detection of cracks can prevent potential damage and failure (12). ...
p>Cracks considerably reduce the life span of pavement surfaces. Currently, there is a need for the development of robust automated distress evaluation systems that comprise a low-cost crack detection method for performing fast and cost-effective roadway health monitoring practices. Most of the current methods are costly and have labor-intensive learning processes, so they are not suitable for small local-level projects with limited resources or are only usable for specific pavement types.
This paper proposes a new method that uses an improved version of the weighted neighborhood pixels segmentation algorithm to detect cracks in 2-D pavement images. This method uses the Gaussian cumulative density function as the adaptive threshold to overcome the drawback of fixed thresholds in noisy environments. The proposed algorithm was tested on 300 images containing a wide range of noise representative of different noise conditions. This method proved to be time and cost-efficient as it took less than 3.15 seconds per 320 × 480 pixels image for a Xeon (R) 3.70 GHz CPU processor to determine the detection results. This makes the model a perfect choice for county-level pavement maintenance projects requiring cost-effective pavement crack detection systems. The validation results were promising for the detection of low to severe-level cracks (Accuracy = 97.3%, Precision = 79.21%, Recall= 89.18% and F1 score = 83.9%).</p
... While some authors included environmental and social aspects in the analysis (Zhang et al. 2010, Torres-Machi et al. 2017, others have suggested that a technical evaluation based on effectiveness indirectly considers social aspects, since larger effectiveness can be translated into increased societal benefit due to the improved condition of the pavement (Torres-Machi et al. 2015). ...
Pavement management systems can be used to efficiently allocate limited maintenance budgets to better align with pavement deterioration. However, pavement deterioration is subject to uncertain factors that complicate the prediction of future pavement conditions accurately, entailing differences in the optimum maintenance strategy. This paper addresses this challenge by introducing a method to aid local engineers in optimising the scheduling of maintenance activities under uncertain pavement deterioration conditions. Markov chains are used to simulate the variability of life-cycle performance. Moreover, a multi-objective optimisation of an urban network is carried out to find the maintenance programme that minimises the mean life-cycle cost, maximises the mean user benefit, and minimises the standard deviation of life-cycle cost. This third objective enables the optimisation routine to minimise the possibility of unintentionally increasing the life-cycle cost due to system variability. This approach results in a reduction of the life-cycle cost variability by up to 62%, provides pavement strategies that benefit road users as a result of better pavement conditions, and reduces the risk of resorting to costly future maintenance activities.
... Unit costs for the different types of pavements and gray road operations were obtained from Mercado Público, the Chilean government's online public procurement platform (Dirección de Vialidad 2014a, b). Green unit costs were acquired from archival literature from Chilean and international sources (Torres-Machí et al. 2015, 2017. This enabled a proper comparison between gray and green procedures within the budgetary limits imposed by the Ministry of Finance. ...
... All these methods have its special utility range and corresponding economic effect. economic and environmental terms [1]. It indicates that the fog seal is the first and the most economical preventive maintenance technology, as well as it has such an outstanding environmental effect. ...
... Assessing the bottom level criteria and multiplying by each weight allows for the assessment of the next criterion level. The process is repeated until the overall decision goal, which is at the top level, is reached [34][35][36][37][38][39]. The AHP assumes the independence of all criteria (outer and inner dimensions), which can be an unrealistic assumption for solving actual real-world problems [40]. ...
The construction of bridges has been necessary for societies since ancient times, when the communication between and within towns, cities or communities was established. Until recently, the economic factor has been the only one considered in the decision-making of any type of construction process for bridges. However, nowadays, the objective should not be just the construction of bridges, but of sustainable bridges. Economic, social and environmental factors, which form the three pillars of sustainability, have been recently added. These three factors usually have conflicting perspectives. The decision-making process allows the conversion of a judgment into a rational procedure to reach a compromise solution. The aim of this paper is to review different methods and sustainable criteria used for decision-making at each life-cycle phase of a bridge, from design to recycling or demolition. This paper examines 77 journal articles for which different methods have been used. The most used methods are briefly described. In addition, a statistical study was carried out on the Multiple Attribute Decision-making papers reviewed.
Inconsistencies between performance data from laboratory‐prepared and field samples have been widely reported. These inconsistencies often result in inaccurate condition prediction, which leads to inefficient maintenance planning. Traditional pavement management systems (PMS) do not have the appropriate means (e.g., mechanistic solutions, extensive data handling facilities, etc.) to consider these data inconsistencies. With the growing demand for sustainable materials, there is a need for more self‐learning systems that could quickly transfer laboratory‐based information to field‐based information inside the PMS. The article aims to present a future‐ready machine learning‐based framework for analyzing the differences between laboratory and field‐prepared samples. Developed on the basis of data obtained from field and laboratory data, the gradient‐boosting decision trees‐based framework was able to establish a good relationship between laboratory performance and field performance ( R ² test > 80 for all models). At the same time, the framework could also show more complex relationships that are often not considered in practice.
Recent studies indicate that deep learning plays a crucial role in the automated visual inspection of road infrastructures. However, current learning schemes are static, implying no dynamic adaptation to users’ feedback. To address this drawback, we present a few-shot learning paradigm for the automated segmentation of road cracks, which is based on a U-Net architecture with recurrent residual and attention modules (R2AU-Net). The retraining strategy dynamically fine-tunes the weights of the U-Net as a few new rectified samples are being fed into the classifier. Extensive experiments show that the proposed few-shot R2AU-Net framework outperforms other state-of-the-art networks in terms of Dice and IoU metrics, on a new dataset, named CrackMap, which is made publicly available at https://github.com/ikatsamenis/CrackMap.
An optimum network-level pavement rehabilitation model has been developed for generating a long-term rehabilitation schedule comprised of a specified number of annual rehabilitation cycles. The optimum model deploys the discrete-time Markov model to predict the performances of both original and rehabilitated pavements wherein the pavement improvement rates are incorporated into the transition probability matrix. The model implements continuous cyclic improvements in the long-term performance curve compared to the traditionally assumed vertical improvements. A Markov chain with (m) condition states can incorporate (m-1) rehabilitation treatments with an expected improvement outcome being the upgrade to condition state (1), the state with best pavement condition. The optimum model deploys an effective decision-making policy that maximizes the long-term pavement performance while minimizing the rehabilitation cycle cost. The optimum model can easily be solved using an appropriate exhaustive search method with functional evaluations. The sample results obtained for a pavement network comprised of (12) highways indicated the efficiency of the proposed optimum model in yielding practical long-term rehabilitation schedules. The sample results also provided the minimal annual budget required to progressively remove the “very poor” pavements that greatly affect the life-cycle cost. Furthermore, investigation of prediction uncertainty resulted in a relatively mild impact when considering lower and upper-limit performance values using 95% confidence level.
A simplified pavement management model for developing a long-term rehabilitation schedule is proposed for flexible pavement. The model deploys the discrete-time Markov model to predict the deterioration of both original and rehabilitated pavement performances. The main objective of the proposed model is to generate optimal annual rehabilitation cycles over a specified analysis period. This objective is achieved by optimising a cost-effectiveness index defined as the ratio of anticipated performance improvement and annual rehabilitation cost. It therefore seeks to find the optimal annual rehabilitation cycle that maximises pavement condition improvement and minimises rehabilitation cost. The corresponding optimum model is subject to a number of constraints that include the non-negativity constraints, upper-limit variable value constraints, and budget constraints. However, the rehabilitation variables are incorporated into the state probabilities rather than the transition matrix when predicting future deterioration of rehabilitated pavement. The optimum model can simply be solved using an exhaustive search approach as it makes use of a limited number of rehabilitation variables. Two case studies are presented to demonstrate the potential uses of the proposed model. The first one examined the relationship between variable budget levels and sustainable long-term pavement performances, whereas the second one investigated the long-term cost-effectiveness of individual rehabilitation treatments. Generally, the sample results re-emphasised the famous theme of ‘better roads at lower costs’.
Based on the publications from two databases during 1998–2020, this paper presents a systematic literature review on pavement maintenance effectiveness evaluation to summarize the current trend and identify the research gap that must be addressed for a sustainable maintenance management. This review has analyzed and synthesized maintenance thresholds and their mechanisms, the measurement methods of effectiveness in terms of performance, cost and environmental impacts. In particular, this paper has critically examined the state-of-art maintenance effectiveness optimization strategy that has included environmental concerns and sustainable goals, in comparison with the traditional cost-effectiveness evaluation method. The study has revealed the ambiguous definition of pavement maintenance effectiveness and data availability have caused inconsistencies in the evaluation process; moreover, the embryonic pavement life cycle assessment studies and limited study on pavement use phase have set obstacles in the expanding system boundary of sustainable maintenance effectiveness evaluation.
Cracks considerably reduce the life span of pavement surfaces. Currently, there is a need for the development of robust automated distress evaluation systems that comprise a low-cost crack detection method for performing fast and cost-effective roadway health monitoring practices. Most of the current methods are costly and have labor-intensive learning processes, so they are not suitable for small local-level projects with limited resources or are only usable for specific pavement types.
This paper proposes a new method that uses an adapted version of the weighted neighborhood pixels segmentation algorithm to detect cracks in 2-D pavement images. The method uses the Gaussian cumulative density function (CDF) as the adaptive threshold to overcome the drawback of fixed thresholds in noisy environments. The proposed algorithm was tested on 300 images containing a wide range of noise representative of various pavement noise conditions. The method proved to be time and cost-efficient as it took less than 3.15 s per 320 × 480 pixels image for a Xeon (R) 3.70 GHz CPU processor to generate the detection results. This makes the proposed method a perfect choice for county-level pavement maintenance projects requiring cost-effective pavement crack detection systems. The validation results were promising for the detection of medium to severe-level cracks (precision = 79.21%, recall = 89.18%, and F 1 score = 83.90%).
Prediction of solvent diffusion and evaporation rate in the initial days after construction of a sprayed seal is of special concern for pavement performance assessment. It is still a major challenge as solvent evaporation is a very complicated process. In this study, laboratory tests were conducted on bitumen-solvent binder films, under different experimental conditions and varying solvent properties. A solution of Fick’s diffusion equation was then used to calculate solvent diffusion coefficient (D) values for the initial 7 days. While a strong correlation was found between D and solvent viscosity as well as D and solvent distillation range, no relationship was found between D and solvent aniline point nor aromatic content. These findings were utilised in developing a multiple linear regression (MLR) diffusion model for the initial 7 days of evaporation. The evaluation of the model indicated close agreement between the predictions and experimental values (R2 = 0.95). The model enables road agencies to predict solvent diffusion and residual solvent for the early life of a sprayed seal without needing to conduct extensive experiments thereby saving time and labour cost. Accurate prediction of residual solvent via the developed model will further ensure long-term performance of sprayed seals.
Hyperspectral image processing techniques, with their ability to provide information about the chemical compositions of materials, have great potential for pavement condition assessment. This study introduces a novel age-based pavement assessment method, employing an integrated algorithm with artificial neural network (ANN) and spectral angle mapping (SAM) on hyperspectral images. In the proposed method, the resulting ANN prediction outputs are used to make a new prediction along with the results from SAM scores. Tests are performed on hyperspectral images that have 360 spectral bands between 400 and 900 nm, collected by a specifically designed vehicular system for proximal image acquisition. The acquired images have eight classes, including three different pavement classes (good (5-year), medium (10-year), and poor (25-year)), yellow dye, white dye, soil, paving stone, and shadow. Several experiments are performed to evaluate the robustness of the followed methodology with limited learning data that include 5, 10, 25, and 50 samples per class, selected randomly from our independent spectral database. For a fair comparison, the individual ANN, SAM, support vector machine (SVM), and stacked auto-encoders (SAE) algorithms are also evaluated. The classification performances of individual ANN and SAM are significantly increased with their joint use, demonstrating a 1.2% to 21% classification accuracy improvement in relation to the training sample size. The study proves that the proposed approach is quite robust in cases wherein few training data are available, while SAE and standard ANN algorithms are more successful in cases wherein more learning data are present.
Low noise, as one of the emerging pavement functions, has received growing interest recently, but was rarely considered in pavement management system. To fill this gap, this study aims to develop a multi-objective optimization (MOO) decision-support system for maintaining the low-noise pavement network system. Three objectives were considered: (1) maximizing the average Close Proximity (CPX) level reduction, (2) minimizing the maintenance costs, and (3) minimizing the greenhouse gas emissions generated from the maintenance. The non-dominated sorting genetic algorithm II (NSGA-II) was employed to search for the optimal intervention strategies. The proposed model was implemented in a case study in Hong Kong to demonstrate its capability. The optimization strategies developed in this study could provide more informative reference for the decision-makers. The best-compromised strategy could be determined by trading off different solution sets subjected to the specific social situations, budget limitations and policy restrictions.
Multiple rating systems have been established to enhance the sustainable design and management of roadway projects. These systems are based on current best practices and demonstrate significant potential for assisting project managers in achieving environmentally sustainable and socially resilient smart transportation assets. HFowever, as it stands there is a significant lack of understanding on these systems, and thus lack of confidence in their implementation. Thus, this study aims to develop an up-to-date critical review on the most prominent rating systems currently in the global market. Specifically, the CEEQUAL, Envision, BE²ST-in-Highways, Greenroads, GreenLITES, Invest and GreenPave systems were selected and analysed in terms of their scopes, structures, common criteria, three-pillar adherence, and asset management effectiveness. The results of this study found: 1) system characteristics can be categorised by system scope (infrastructure, roadway or pavement) and assessment type (self-assessment or third-party, 2) third-party systems assessed the three-pillars of sustainability and the identified macro-categories more homogeneously, and 3) rating systems show strong potential for the social assessment of projects, but their consideration of life-cycle assessment could be more outcome-orientated. Future work should apply the rating systems to project case studies to further identify implementation, contextual and indicator pluralism issues.
Aged road pavements and insufficient maintenance budgets, along with increasing concerns over the environmental issues related to transportation have introduced additional challenges to highway agencies. Multiobjective optimisation techniques can be used to account for those multiple aspects in the design of maintenance and rehabilitation (M&R) strategies. Contrary to the singleobjective optimisation problems where a single solution is optimal, the solution of multiobjective optimisation problems is a set of non-dominated solutions, often referred to as Pareto-optimal set. This set of optimal solutions represents the trade-off between the different and often conflicting objectives, and in many cases is comprised by a vast number of elements. This paper presents the development and application of a fuzzy logic expert system for selecting a single solution from the Pareto set obtained from the multiobjective optimisation of sustainable pavement M&R strategies. It provides decision-makers with an easy and intuitive methodology for the selection of the most preferred solution according to sustainability criteria. The proposed system is applied to a case study from France. Posteriorly, different strategies reflecting the decision-maker’s preferences towards economic and environmental objectives are analysed. Conclusions and recommendations for future improvements are derived from this application.
Ideally, a complete bond between the chip-seal and asphalt pavement is achieved during the chip-seal application. However, complete and total bonding is unlikely due to environmental and material conditions. Therefore, it is critical to understand the bond qualities under varying environmental and material conditions, which is also beneficial for cleaner production of chip-seal applications. The shear bond strength is a crucial indicator for revealing the bond qualities of chip-seal with asphalt pavement. The objective of this study is to develop a laboratory approach to characterise the shear bond strength of a chip-seal application with the asphalt pavement. It is achieved by developing a laboratory approach to the shear bond test (SBT). This study investigated the shear bond strength between chip-seal and asphalt pavement of several asphalt-aggregate combinations and different asphalt-emulsion application rates. Also, in order to characterise the influence of temperatures and freeze–thaw cycles on the durability of chip-seal, several test temperatures, and the multiple freeze–thaw cycles were applied in the proposed SBT. The laboratory test outcomes recommended that the weak shear bonding of chip-seal with asphalt pavement is in part because of the multiple freeze–thaw cycles suffered and the raw materials used.
In order to minimize the total expected cost, bridges have to be designed for safety and durability. This paper considers the cost, the safety, and the corrosion initiation time to design post-tensioned concrete box-girder road bridges. The deck is modeled by finite elements based on problem variables such as the cross-section geometry, the concrete grade, and the reinforcing and post-tensioning steel. An integrated multi-objective harmony search with artificial neural networks (ANNs) is proposed to reduce the high computing time required for the finite-element analysis and the increment in conflicting objectives. ANNs are trained through the results of previous bridge performance evaluations. Then, ANNs are used to evaluate the constraints and provide a direction towards the Pareto front. Finally, exact methods actualize and improve the Pareto set. The results show that the harmony search parameters should be progressively changed in a diversification-intensification strategy. This methodology provides trade-off solutions that are the cheapest ones for the safety and durability levels considered. Therefore, it is possible to choose an alternative that can be easily adjusted to each need.
To enhance concern for the social aspects of sustainability and to delineate the criteria to be considered at each stage of the lifecycle of an infrastructure, this paper aims to determine the relevance of a set of criteria that evaluate social sustainability throughout the lifecycle of a public civil infrastructure. This research presents the results of a case study applying the Delphi method to 24 Chilean experts consulted in a series of three rounds. In addition, binomial statistical tests and Kendall's coefficient were used to show the convergence of the experts. Thus, it was identified that of 36 initial criteria assessed at each stage of the lifecycle, the consideration of 20 is required at the design stage, 29 at the construction stage, 33 during operation, and 27 at demolition. The most relevant criteria, per lifecycle stage, were Stakeholder Participation (design and demolition stages), External Local Population (design stage), Internal Human Resources (construction and demolition stages), Macro-Social Action of Socioenvironmental Activities (construction stage), and Macro-Social Action of Socioeconomic Activities (operation stage).
Ground transportation infrastructures, particularly road infrastructure, are essential for economic and social development. The quality level that the user perceives is mainly determined by the pavement condition. More than 400 billion dollars are invested globally each year in pavement construction and maintenance; these tasks increase by 10% the environmental impact generated by vehicle operation. Therefore, a sustainable approach should be incorporated in the assessment of preservation alternatives that consider technical, economic, environmental, political and institutional aspects in an integrated manner over their life-cycle. The purpose of the present research is to examine the models and practices for the economic and environmental evaluation of pavement assets, in order to analyze the advantages and limitations of the current state of the practice and identify the opportunities to improve their sustainable management. One of the main limitations identified is the lack of models that consider the economic and environmental aspects integrally. A need for models which consider the impact on users in work zones, as well as the use of new technologies and recycled materials that are more respectful of the environment, has been detected.
The objective of this study was to compile experiences regarding efforts by road authorities to satisfy the needs for efficient maintenance and the results of such efforts. The extent to which maintenance aspects are considered during road planning and design, as a potential for improvement of maintenance efficiency is studied. The study shows that such efforts have in many cases resulted in reduced maintenance costs. However, there are also indications that maintenance standards in some cases have declined, as the focus has been on reduction of the rate of recurring maintenance activities and prioritisation of some maintenance measures, e.g. winter maintenance, over other maintenance measures, e.g. pavement maintenance. The study also shows that efforts towards increased maintenance efficiency have one thing in common - namely that the main focus has been on improving operating practices and maintenance procedures. Road authorities have mostly ignored the improvement potentials that exist during the planning and design process through consideration of the interrelationship between geometrical road design and maintenance.
Research in Bid Tender Forecasting Models (BTFM) has been in progress since the 1950s. None of the developed models were easy-to-use tools for effective use by bidding practitioners because the advanced mathematical apparatus and massive data inputs required. This scenario began to change in 2012 with the development of the Smartbid BTFM, a quite simple model that presents a series of graphs that enables any project manager to study competitors using a relatively short historical tender dataset. However, despite the advantages of this new model, so far, it is still necessary to study all the auction participants as an indivisible group; that is, the original BTFM was not devised for analyzing the behavior of a single bidding competitor or a subgroup of them. The present paper tries to solve that flaw and presents a stand-alone methodology useful for estimating future competitors’ bidding behaviors separately.
Deterioration indexes that may combine types of surface distresses, serviceability, and structural indicators are commonly used for pavement management at the network level. These indexes differ in the types of deterioration and criteria considered to quantify severity and density of distresses. Most of these indexes were developed for interurban road networks; therefore, their application to urban networks is complex and not representative. For this reason, there is a need for a better understanding of urban pavement behavior to enable collection of the distresses relevant to these types of pavements and development of an overall condition index for urban pavements that represents the mix of the more relevant distresses for use in network analysis. This study is part of a 3-year project developed in Chile: Research and Development of Solutions for Urban Pavement Management in Chile. The main objective of this study was to calibrate and to validate an urban pavement condition index (UPCI) representative of the overall condition of these pavements, according to objective measures of surface distresses and evaluations of an expert panel. The scope of this study included the development of distress evaluation guidelines for asphalt and concrete pavements considering manual and automated surveys, the application of these guidelines in different types of urban networks, and the assessment of these networks by an expert panel. Finally, three UPCI equations were obtained with satisfactory validation for asphalt pavements with manual and automated data collection and for concrete pavements with manual data collection.
Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach.
When exposed to destructive climate and weather factors and heavy vehicle loads, the pavement wears and deflects. In recent decades, apart from cracks and potholes, the depth of ruts grows and makes an increasing share of the pavement surface. The deeper are the tracks, the poorer are traffic conditions for fast-moving cars: drivers are struggling, speed is decreasing and the number of accidents is increasing. After track depth reaches a critical and permissible limit, the road surface must be repaired or speed limit has to be reduced. The work presents a theoretical analysis of track emergence causes and factors determining their depth. With the help of Mobile Road Research Laboratory RST 28, the track depth of all Lithuanian highways has been measured every 20 metres. The obtained data have been processed using the methods of mathematical statistics. Each road has a sample average of every rut, sample standard deviation and a coefficient of individually measured variation. The paper has drawn histograms, calculated skewness, kurtosis and normal distribution and provided lognormal distribution curves of a probability density function. The visualisation and empirical skewness and kurtosis values have revealed that the depth of the rut distributes according to lognormal rather than normal distribution. The average values of the roads having a dividing strip and standard deviations from the distribution across the road have been received. The given dependence of the rut depth of a standard deviation on the averages of rut depth shows an elastic interface of these parameters (determination coefficient R2= 0.741).
Purpose
Although a significant number of environmental protection measures concerning industrial products and processes have emerged over the past few years, similar measures have only started to appear in road construction and related practices. There is a need for understanding what a “sustainable pavement” would entail in terms of greenhouse gas emissions and energy consumption. Since environmental impact assessment of major projects is becoming mandatory in many countries, various research projects attempt to evaluate the environmental impact of different pavement materials, technologies, or processes over the road life cycle. To support these efforts, there is a need to measure and describe different aspects of sustainability related to road pavements. In particular, keeping road pavements at high service levels through a preventive maintenance approach during the pavement service life has been proven to provide significant improvement of their performance and reduce their deterioration rate.
Methodology
This paper describes an innovative methodology to evaluate the environmental impact of preventive maintenance activities. It relates these activities to performance and cost during the service life of the pavement through a multi-attribute “life cycle cost, performance, and environmental analysis”. Emissions and energy saved adopting several preventive maintenance strategies were computed, relating them to cost and performance. Equipment and materials usually involved in road maintenance practices were also analyzed in order to assess specific fuel consumption and energy spent. An ad hoc index was ultimately created, adopting a script file to evaluate the best strategy through the multi-attribute approach.
Results and conclusions
Results show how eco-effective it can be to improve pavement management practices on roads by implementing energy efficient treatments and strategies. Furthermore, eco-saving factors could represent a new and innovative feature to be added in the sustainability assessment process for pavements to evaluate different alternatives and assist authorities choosing between different investment solutions as a part of a decision support system.
Modeling pavement performance and optimizing resources represent two challenges for decision makers responsible for maintenance and rehabilitation of road networks pavement. This paper presents the developments made in a stochastic performance prediction model and optimization model as two major parts of an integrated pavement management system. Markov modeling is used to create a transition process model that is implemented to predict pavement condition throughout the life time of road networks. With the use of the Pavement Condition Index (PCI), the steps of performing the prediction of deterioration are presented, showing the process of creating the elements of Markov matrix. The obtained results are used to set the priorities for maintenance planning and budgeted cost allocations on the network level. The proposed model advises decision makers on the status of network level with the guidelines to keep road conditions in acceptable level of performance according to the predefined strategies. Genetic algorithms technique is adopted to build optimization model. Three objective functions are constructed for budgeted cost of maintenance and rehabilitation program, quality of work performed, and selected area for program implementation. A brief description of the developed pavement management systems, including the prediction and the optimization models, are presented. A numerical example is worked out to illustrate the practical use of both models.
Economy and nonproductive sectors of each country could not function without a transport system (TS). Having analysed research works on the interaction of separate TS elements, it was identified that there is no common model for all types of interaction. TS consists of material (physical) objects: traffic participants and freight to be carried, a transportation process and operations’ control. TS classification scheme devised according to systematically selected criteria, showing that several criteria are often applied at the same time in official documents, is presented. Original TS physical elements’ interaction model with 6 interaction levels is presented as well. The model is suitable for all modes of transport. Six levels of interaction are distinguished: autointeraction of transport elements, the first level; TS elements’ interaction, the second level; TS elements’ interaction with external environment, the third level; interaction of transport modes, the fourth level; TS interaction with the country's economy and nonproductive sectors, the fifth level; and TS impact on the country's GAV (Gross Added Value), the sixth level. Properties and factors influencing on the results and parameters of interaction have been systematized. Levels and properties of interaction have been analyzed as well. To evaluate the importance of interaction levels to the parameters of the transportation process, the method of Analytic Hierarchy Process (AHP) has been recommended.
It is becoming increasingly necessary in life-cycle analysis (LCA) of infrastructure assets, including pavements, to take a longer-term approach than has been used, mainly to ensure sustainability and assess the impacts of today's decisions accurately. LCA can include primarily life-cycle cost analysis (LCCA), but it also can include considerations of resource conservation, environmental impacts, energy balance, and so forth, and it can involve short-, medium-, and long-term periods. It is thus possible to develop a context for LCA of likely and uncertain societal activities, including transportation, over these periods. Conventional LCCA is directed toward comparing competing alternative investment strategies and can involve a range of stakeholders. Of the methods available, present worth of costs is almost exclusively used in the pavement field. However, when medium- to longer-term life-cycle periods are involved, rate-of-return and cost-effectiveness formulations can be applicable. A numerical example shows how an agency can determine the internal rate of return for two investment alternatives involving different pavement designs and a life-cycle period of 50 years. In addition, a cost-effectiveness example is provided for a sidewalk network, again with a life-cycle period of 50 years. Conventional LCCA for calculating present worth of costs will undoubtedly continue to be used in the pavement field as a primary tool. However, using a rate-of-return or cost-effectiveness formulation, especially for medium- to longer-term life-cycle periods, should be given more consideration.
Multicriteria analysis (MCA) provides a framework for breaking a problem into its constituent parts. MCA provides a means to investigate a number of alternatives in light of conflicting priorities. By structuring a problem within the MCA framework, alternatives may be ranked according to preestablished preferences to achieve defined objectives. A method developed for providing an MCA framework within the Highway Development and Management Tools, Version 4 (HDM-4) is described. Factors such as social benefits, environmental effects, safety impact, strategic importance of roads, and so forth have been included, within a unified decision-making framework. The analytic hierarchy process method was selected for HDM-4 because it transforms the analysis of competing objectives to a series of simple comparisons between constituent elements. The approach does not require a definition of tradeoffs between the possible values of each attribute (i.e., it is not necessary to build utility functions), and it allows users to understand how outcomes are reached and how weightings influence outcomes. A pilot implementation checked the applicability of the analytical hierarchy process (AHP) method to road management and analyzed the effectiveness of outputs. Results obtained using HDM-4 economic criteria were compared with those produced by AHP. For the pilot implementation, the HDM-4 strategic planning application was chosen because it is the level in which, generally, medium- or long-term programs must be defined along with economic and other social and environmental aspects to justify budget allocations. Five main criteria were identified with regard to road maintenance budget allocations that constrain the decision-making process: comfort, environment, safety, road agency costs, and road user costs. Prioritization based on MCA more evenly distributes the available budget when compared with prioritization based on economic criteria, which tends to favor roads with high volumes of traffic.
This paper describes a methodology in designing high-performance concrete for simply supported beams, using a hybrid optimization strategy based on a variable neighborhood search threshold acceptance algorithm. Three strategies have been applied to discrete optimization of reinforced concrete beams: Variable Neighborhood Descent (VND), Reduced Neighborhood Search (RNS) and Basic Variable Neighborhood Search (BVNS). The problem includes 14 variables: two geometrical; one material type; one mix design; and 10 variables for the reinforcement setups. The algorithms are applied to two objective functions: the economic cost and the embedded CO2 emissions. Firstly, this paper presents the application of these three different optimization strategies, which are evaluated by fitting the set of solutions obtained to a three-parameter Weibull distribution function. The Variable Neighborhood Descent with Threshold Accepting acceptance strategy algorithm (VND-TA) results as the most reliable method. Finally, the study presents a parametric study of the span length from 10 to 20 m in which it can be concluded that economic and ecological beams show a good parabolic correlation with the span length.
To appropriately mitigate environmental impacts from transportation, it is necessary for decision makers to consider the life-cycle energy use and emissions. Most current decision-making relies on analysis at the tailpipe, ignoring vehicle production, infrastructure provision, and fuel production required for support. We present results of a comprehensive life-cycle energy, greenhouse gas emissions, and selected criteria air pollutant emissions inventory for automobiles, buses, trains, and airplanes in the US, including vehicles, infrastructure, fuel production, and supply chains. We find that total life-cycle energy inputs and greenhouse gas emissions contribute an additional 63% for onroad, 155% for rail, and 31% for air systems over vehicle tailpipe operation. Inventorying criteria air pollutants shows that vehicle non-operational components often dominate total emissions. Life-cycle criteria air pollutant emissions are between 1.1 and 800 times larger than vehicle operation. Ranges in passenger occupancy can easily change the relative performance of modes.
It is becoming increasingly necessary in life-cycle analysis (LCA) of infrastructure assets, including pavements, to take a longer-term approach than has been used, mainly to ensure sustainability and assess the impacts of today's decisions accurately. LCA can include primarily life-cycle cost analysis (LCCA), but it also can include considerations of resource conservation, environmental impacts, energy balance, and so forth, and it can involve short-, medium-, and long-term periods. It is thus possible to develop a context for LCA of likely and uncertain societal activities, including transportation, over these periods. Conventional LCCA is directed toward comparing competing alternative investment strategies and can involve a range of stakeholders. Of the methods available, present worth of costs is almost exclusively used in the pavement field. However, when medium- to longer-term life-cycle periods are involved, rate-of-return and cost-effectiveness formulations can be applicable. A numerical example shows how an agency can determine the internal rate of return for two investment alternatives involving different pavement designs and a life-cycle period of 50 years. In addition, a cost-effectiveness example is provided for a sidewalk network, again with a life-cycle period of 50 years. Conventional LCCA for calculating present worth of costs will undoubtedly continue to be used in the pavement field as a primary tool. However, using a rate-of-return or cost-effectiveness formulation, especially for medium- to longer-term life-cycle periods, should be given more consideration.
Every year, American drivers spend hundreds of billions of dollars on highway transportation. They pay for vehicles, maintenance, repair, fuel, lubricants, tires, parts, insurance, parking, tolls, registration, fees, and other items. These expenditures buy Americans considerable personal mobility and economic productivity.
In developed countries, the need of infrastructure maintenance is becoming an important issue because their infrastructures have been built up progressively over the last 100 years or longer. Moreover, users are increasingly demanding in terms of quality, comfort, and safety. Under this scenario, infrastructure managers seek to optimize each monetary unit invested in maintenance, thus ensuring that funds are allocated to the best alternative. This paper presents a heuristic model for solving the budget allocation problem with the implementation of a Simulated Annealing (SA) algorithm. An illustrative example is undertaken, analyzing the effect of budgetary restrictions in infrastructure performance. It can be concluded that infrastructure performance shows a good parabolic correlation with available budget.
Unpaved roads play a crucial role in the economic and social development of societies, linking rural communities to education, health services, and markets. The asset value of unpaved roads is low compared with national and provincial road networks, because agencies responsible for rural roads management lack the resources to assess and maintain the network properly. Lack of resources is especially critical in developing countries, where the majority of the population lives in rural areas and where few tools are available for sustainable management of the unpaved network. The main objective for this study was to develop and validate cost-effective maintenance standards for unpaved rural roads. The study was directed at improving the management process of unpaved road networks that serve rural populations. The scope was to develop maintenance standards that can be used by agencies in charge of network management, given available resources and technical skills. The developed four-step methodology evaluates an unpaved road network for 4 years, identifies the effects of maintenance treatments on the condition of roads from field data analysis, defines maintenance strategies, and develops optimal maintenance standards. The study was part of a 4-year project conducted at the University of Waterloo, in Ontario, Canada, that resulted in the development of a sustainable management system for rural road networks in developing countries. The proposed standards were applied and successfully validated and were demonstrated to be adaptable to varying climates, budgets, traffic, and road structures.
This paper serves as an introduction to the Analytic Hierarchy Process - A multicriteria decision making approach in which factors are arranged in a hierarchic structure. The principles and the philosophy of the theory are summarized giving general background information of the type of measurement utilized, its properties and applications.
Structures deteriorate as a result of material aging, aggressive environmental conditions, and increasing loads. During their lifetime, structures are also possibly exposed to some extreme events. The associated consequences of failure caused by progressive deterioration or extreme events can be devastating. Therefore, risk assessment and risk mitigation are necessary to keep structural performance within tolerable levels. This paper proposes an approach for assessing the time-dependent risks caused by traffic and earthquake loads and establishing the optimal preventive and essential maintenance strategies of bridges. The efficiency of the proposed approach is demonstrated using a highway bridge. Socioeconomic and environmental losses are investigated in a consequence-based framework. The vulnerability analysis under traffic loads is performed using time-dependent deterioration and traffic load models. The time-dependent failure probability for given earthquake loads is computed by comparing displacement ductility capacity and demand obtained via nonlinear dynamic analysis. The risks from 196 earthquake scenarios associated with four magnitudes and 49 earthquake strike locations are compared, and the highest one is selected as representative of the seismic risk. Based on the available maintenance options and the associated costs, the optimal lifetime essential/preventive maintenance strategies for total risk mitigation are developed.
Sustainability is characterized as a three-legged stool supported by economic, environmental, and social considerations. This paper demonstrates the feasibility of integrating environmental performance measures, one aspect of sustainable practices, into asset and pavement management. To illustrate these concepts, a Microsoft Excel workbook-based pavement construction decision support tool named Pavement Life-Cycle Assessment Tool for Environmental and Economic Effects (PaLATE) is introduced. Background information is given on life-cycle assessment (LCA) pavement construction tools. PaLATE product life-cycle and LCA phases are covered, in addition to PaLATE data and data sources. Atable describing the data used for environmental calculations is included, and the use of an asphalt emulsion seal and the use of an ultrathin hot-mix asphalt overlay are compared by use of the tool. Special attention is given to recycled materials and environmental measures. Concluding remarks suggest different contexts for potential applications of PaLATE, together with network tools that can be used to meet user needs and applications as well as to address feasibility and cost.
Today, public agencies responsible for roads, streets, and highways are experiencing significant increases in the price of construction operations and asphalt binder availability; they are also experiencing limited available funds and the uncertainty of inflation. Those concerns are coupled with significant pressure to build, maintain, and rehabilitate "green," and agencies must look to alternative construction, rehabilitation, and maintenance methods as well as alternative materials that deliver on both of these seemingly different forces. Life-cycle assessment was used to evaluate roadway construction activities. Life-cycle assessment is similar to life-cycle cost analysis, except that environmental impact is considered over the analysis period. Life-cycle assessment includes energy consumption, emissions generation, and natural resource consumption in addition to price of the activity. All activities evaluated were compared with conventional materials and means of construction. Materials evaluated specific to hot-mix asphalt included reclaimed asphalt pavement, asphalt shingles, and warm-mix asphalt. Aggregate base stabilization and subgrade treatments were evaluated as part of a low- and high-traffic-volume facility. The final evaluation considered rehabilitation and maintenance activities that focused on in-place recycling, such as hot in-place and cold in-place recycling. In most instances, these activities can reduce energy consumption and emissions generation and can conserve natural resources (aggregate and asphalt binder), plus offer the benefit of reducing the price of construction. These materials and technologies show promise in helping agencies meet the rising price of construction while addressing public concern for the environment.
The Centre for Pavement and Transportation Technology at the University of Waterloo and the Ministry of Transportation of Ontario (MTO) have been studying for the past 4 years the suitability of applying automated technologies for network-level evaluations in the province. Three projects have been developed for this purpose. The main results of these studies were a better understanding of available digital technologies, evaluation of the performance of semiautomated and automated technologies, development of new guidelines for pavement distress collection at the network level, design of an adjusted distress manifestation index, and recommendations for the use of semiautomated and automated digital technologies at the network level. The objective of this paper is to present the findings of the third and last phase of the project, Validation and Implementation of MTO Network Level Automated-Semiautomated Pavement Distress Guidelines and Condition Rating Methodology. The scope of the study was to validate and implement in the field MTO network-level distress guidelines and a distress manifestation index for network-level evaluations (DMI NL), considering the use of automated technologies. A complete statistical analysis of data collected in the field through manual evaluations and semiautomated and automated technologies is presented. The performance of currently available technologies using network-level distress guidelines was assessed. Finally, from the field validation, distress guidelines were adjusted accordingly and DMI NL equations were recalibrated.
This paper presents the development and implementation of a Multi-Objective Decision-Aid Tool (MODAT) tested with data from the Estradas de Portugal's Pavement Management System. The MODAT uses a multi-objective deterministic section-linked optimisation model with different possible goals: minimisation of agency costs, minimisation of user costs, maximisation of the residual value of pavements, etc. The MODAT also uses the deterministic pavement performance model used in the AASHTO flexible pavement design method. The application of the new Decision-Aid Tool is illustrated with a case study involving the main road network of Castelo Branco, a district of Portugal. In this application, the Knee point, that represents the most interesting solution of the Pareto frontier, corresponds to an agency costs weight value of 4% and an user costs weight value of 96%, demonstrating that user costs, which are generally much higher than agency costs, dominate the decision process.
Optimization-based tools have been included in many engineering management systems for individual infrastructure asset classes such as pavement management systems (PMS) and bridge management systems (BMS). These tools typically include single-objective optimization analyses. However, real-world decisions concerning asset preservation and renewal often involve more than one objective reflecting the various goals of the agency and need to evaluate possible alternatives according to multiple criteria. Traditional single-objective optimization approaches for handling such situations optimize a selected most important objective while either neglecting the less important competing objectives or imposing them as known constraints in the optimization formulation. This approach often does not provide truly optimal solutions. Multiobjective optimization formulations have clear theoretical advantages but increase the complexity of the mathematical formulation. This paper presents a review of the application of multiobjective optimization techniques in various working levels of highway asset management. Some promising techniques for the different infrastructure management functions are identified, and relevant characteristics are summarized and compared. Based on the applications reviewed, it can be concluded that multiobjective optimization could be effective for supporting many infrastructure management business processes. The review also suggests that a synergistic integration of complementary techniques may help develop practical and efficient decision-supporting tools that take advantage of the benefits and avoid potential drawbacks of the individual techniques.
This paper tackles the problem of allocating medical students to clinical specialities over a number of time periods. Each speciality is offered by a number of consultant led ‘firms’ and the objective is to optimise the schedule in terms of ensuring a broad range of experience for each student, whilst ensuring that every student covers every speciality exactly once without exceeding the number of places available in each firm. The balance between feasibility and optimality is a key issue. We develop a family of GRASP heuristics for the problem, all based on the same local search heuristic, but using a variety of constructions. These use different building blocks, different score functions, and different ways of balancing feasibility and optimality. Empirical tests show that the best heuristic, based on large building blocks facilitated by the use of a network flow model, and enhanced by feedback in the form of partial reconstructions, performs extremely well on real data, and is able to produce acceptable solutions on more challenging artificial problem instances.
Roadway pavement maintenance is essential for driver safety and highway infrastructure efficiency. However, regular preventive maintenance and rehabilitation (M&R) activities are extremely costly. Unfortunately, the funds available for the M&R of highway pavement are often given lower priority compared to other national development policies, therefore, available funds must be allocated wisely. Maintenance strategies are typically implemented by optimizing only the cost whilst the reliability of facility performance is neglected. This study proposes a novel algorithm using multi-objective particle swarm optimization (MOPSO) technique to evaluate the cost-reliability tradeoff in a flexible maintenance strategy based on non-dominant solutions. Moreover, a probabilistic model for regression parameters is employed to assess reliability-based performance. A numerical example of a highway pavement project is illustrated to demonstrate the efficacy of the proposed MOPSO algorithms. The analytical results show that the proposed approach can help decision makers to optimize roadway maintenance plans.
During the past decade, considerable efforts have been made to valuate the benefits of investments in rural roads in developing countries. Although the outputs of those studies have led to a global rethinking of traditional road appraisal methods, limited attempts have been made to integrate these findings into the rural road management process. The problem that arises from the analysis is a missing link between the appraisal of the socioeconomic impact and the management of rural roads. The main objective of the present study was to develop a methodology that combined all key aspects required for the sustainable management of rural roads in developing countries. For this, social, technical, economic, political, and sustainability aspects must be considered at the different levels of the management process. A case study developed in Chile is presented to illustrate the application of the proposed framework at the strategic and the network levels. From the application it was concluded that it was possible to combine in a practical and integrated tool all key factors affecting the process of management of rural roads in developing countries.
Various transportation agencies have begun to consider implementing preventive maintenance (PM) strategies as part of their regular pavement management programs. To determine whether a PM strategy is more cost-effective than a conventional maintenance strategy, various technical and economic analyses were carried out. Currently, most agencies have limited information on the cost-effectiveness (CE) and long-term performance of PM strategies, so it is difficult to determine when and where these treatments should be used. The use of PM treatments based on a CE calculation and analysis is examined, and a decision tree (including treatments and strategies) is developed for each functional pavement class of the Ontario road network. Pavement data from the Ministry of Transportation of Ontario are used to perform a CE calculation for each suggested PM treatment and strategy. On the basis of a comparison and analysis of CE calculation results, guidance is provided on the right treatment, time, and strategy cost level for each functional pavement PM program within the Ontario environment. The results are summarized in the form of a decision tree.
Pavement preservation programming often involves multiple objective considerations. Traditional single-objective optimization frameworks consider one single objective while imposing competing objectives as constraints in the optimization formulation. This paper proposes an approach for pavement preservation programming that uses multiobjective optimization and chance constraints. This approach can handle multiple incommensurable and conflicting objectives while considering probabilistic constraints related to the available budget over the planning horizon. The implementation of the approach in a case study with two conflicting objectives of: (1) maximizing the network level of service in terms of weighted average state condition; and (2) minimizing the total preservation cost, shows that its application provides a practical and flexible tool to determine optimal allocation of resources for pavement preservation that reflects agency goals, resource limitations, and performance targets.
A three-step local search algorithm based on a probabilistic variable neighborhood search is presented for the vehicle routing problem with a heterogeneous fleet of vehicles and soft time windows (VRPHESTW). A generation mechanism based on a greedy randomized adaptive search procedure, a diversification procedure using an extinctive selection evolution strategy, and a postoptimization method based on a threshold algorithm with restarts are considered to solve the problem. The results show the convenience of using an economic objective function to analyze the influence of the changes in the economic environment on the transportation average profit of vehicle routing problems. Near real-world vehicle routing problems need (1) an economic objective function to measure the quality of the solutions as well as (2) an appropriate guide function, which may be different from the economic objective function, for each heuristic method and for each economic scenario.
This paper presents a stochastic dynamic programming (DP) procedure for multiobjective optimization of bridge network maintenance planning that involves a group of existing highway bridges with various remaining service lifetimes and different reliability importance factors to the bridge network. The complex multiobjective optimization problem is solved by using a two-phase DP approach. The Phase I problem consists of identifying the optimal maintenance plans for individual bridges that have minimum life-cycle maintenance costs, while satisfying both condition and safety requirements for a targeted service lifetime period. This problem is solved by using a specific DP optimization algorithm along with Monte Carlo simulation. The Phase II problem is to rationally allocate the limited annual maintenance budgets in such a way that the identified optimal maintenance plans for individual bridges can be satisfied for as many bridges as possible. A single-objective formulation derived from multiple attribute utility theory with weight assignment from reliability importance factors is developed. This is solved by a binary integer programming algorithm. The ultimate goal of this study is achieved in terms of finding the most efficient combinations of available maintenance actions applied to all bridges in a highway network.
Resource management ensures that a project is completed on time and at cost, and that its quality is as previously defined; nevertheless, resources are scarce and their use in the activities of the project leads to conflicts in the schedule. Resource leveling problems consider how to make the resource consumption as efficient as possible. This paper presents an Adaptive Genetic Algorithm for the Resource Leveling Problem, and its novelty lies in using the Weibull distribution to establish an estimation of the global optimum as a termination condition. The extension of the project deadline with a penalty is allowed, avoiding the increase in the project criticality. The algorithm is tested with the Project Scheduling Problem Library PSPLIB. The proposed algorithm is implemented using VBA for Excel 2010 to provide a flexible and powerful decision support system that enables practitioners to choose between different feasible solutions to a problem in realistic environments.
A new time-domain method for separating incident and reflected waves in wave flumes using any number of wave gauges is presented. The method (named LASA) is based on a local approximation model considering linear and Stokes II nonlinear components, and a simulated annealing algorithm to calculate the parameters of the local approximation model. The LASA method is directly applicable to experiments in wave flumes with an arbitrary number of wave gauges, but the LASA concept may be extended to laboratory and field three-dimensional experiments by selecting the appropriate local approximation model. The LASA method has been compared to the two-point and Kimara's method and has proved to be very robust. The application of the LASA method to physical experiments using nonstationary regular and random waves generated estimations of incident and reflected waves with relative mean squared errors lower than 3% for regular waves and ranging from 4 to 16% depending on the spectral shape.
Decision makers are always faced with the challenge of selecting and implementing cost-effective pavement preservation alternatives, particularly when encountering shrinking budgets and increased competition for funds. Pavement intervention and investment evaluation criteria used in past research and practice are reviewed. The synthesis of pavement preservation effectiveness and efficiency evaluation techniques that is presented is unique from both benefit and cost perspectives. Criteria are of the following categories: effectiveness (benefit) only, cost only, cost-effectiveness, and economic efficiency. Computational details, past applications, merits, and demerits of various evaluation criteria are discussed for each criterion. Then selected criteria are computed with data from a national pavement study; they are used to evaluate alternative rigid pavement rehabilitation treatments. The case study results suggest that the superior short-term effectiveness exhibited by a treatment does not necessarily translate into superior long-term effectiveness. The evaluation results can vary widely for cost only, effectiveness only, and both cost and effectiveness criteria. Thus, evaluation based on cost-only or effectiveness-only criteria can yield biased evaluation results. To be a suitable candidate, a treatment or strategy must be not only effective but also cost-effective and economically efficient and the incorporation of user costs into evaluation can significantly influence the evaluation results. Such a synthesis can be a vital support for highway agencies in decision making for infrastructure management in general and pavement management in particular.
Pavement management systems PMSs are increasingly important tools in the decision-making processes regarding the maintenance and rehabilitation of road pavements. A new optimization model to be used within network-level PMSs is presented in this paper, together with a genetic-algorithm heuristic to solve the model. The model assumes decisions to be segment linked, thus overcoming the principal drawback of the widely used Arizona PMS. The objective of the model is to minimize the expected total discounted costs of pavement maintenance and rehabilitation actions over a given planning time span, while keeping the network within given quality standards. The model was applied to three test problems involving the road network of Coimbra, the third-largest Portuguese city. The results obtained for these problems clearly indicate that the model is a valuable addition to the road engineer's toolbox.
This article discusses how to efficiently and completely solve a bi-objective pavement maintenance and rehabilitation-scheduling problem, which aims at optimizing two objectives of pavement condition improvement and budget utilization in a simultaneous manner. This problem may be addressed by the weighting method, constraint method, ranking method, and various metaheuristic methods. However, none of these methods can guarantee the complete Pareto-optimal solution set, which would potentially lead to suboptimal decisions. In this article, a parametric method is suggested to solve the bi-objective pavement maintenance and rehabilitation-scheduling problem. The effectiveness and efficiency of the parametric method is investigated and demonstrated through a case study using the real-world data set from the Dallas District's Pavement Management Information System. A performance comparison between the widely used weighting method and the parametric method clearly justifies the computational advantages of the parametric method.
After an enormous investment in construction of highway networks undertaken in the second half of the 20th century, the highway networks of most European and North American countries are now completed or close to completion. As a result, the need in funding changed from building new highway structures to repair, rehabilitation, and replacement the existing ones. In this paper, a model for analyzing the evolution in time of probabilistic performance indicators of existing structures, in terms of condition, safety, and cost under no maintenance, preventive maintenance, and essential maintenance, is presented. This model integrates the current practice in bridge management systems based on visual inspections (condition index) with structural assessment (safety index) during the lifetime of existing structures. The proposed model allows the consideration of uncertainties in the performance deterioration process, times of application of maintenance actions, and in the effects of maintenance actions on the condition, safety, and life-cycle cost of structures by defining all parameters involved in the model as random variables. Interaction between condition and safety profiles is defined through probabilistic and deterministic relations. The probabilistic characteristics of the condition, safety, and cost profiles of deteriorating structures are computed by Monte-Carlo simulation. Several realistic examples, based on data on highway bridge components gathered in the United Kingdom, are presented.
An efficient probabilistic set covering heuristic is presented. The heuristic is evaluated on empirically difficult to solve set covering problems that arise from Steiner triple systems. The optimal solution to only a few of these instances is known. The heuristic provides these solutions as well as the best known solutions to all other instances attempted.
A new general purpose algorithm for the solution of combinatorial optimization problems is presented. The new threshold accepting method is even simpler structured than the wellknown simulated annealing approach. The power of the new algorithm is demonstrated by computational results concerning the traveling salesman problem and the problem of the construction of error-correcting codes. Moreover, deterministic (!) versions of the new heuristic turn out to perform nearly equally well, consuming only a fraction of the computing time of the stochastic versions. As an example, the deterministic threshold accepting method yields very-near-to-optimum tours for the famous 442-cities traveling salesman problem of Grötschel within 1 to 2 s of CPU time.
In this article, we propose a meta-heuristic algorithm for solving multi-objective combinatorial optimization problems. The proposed multi-objective combinatorial optimization algorithm is developed by combining the good features of popular guided local search algorithms like simulated annealing (SA) and tabu search (TS). It has been organized as a multiple start algorithm to maintain a good balance between intensification and diversification. The proposed meta-heuristic algorithm is evaluated by solving the stacking sequence optimization of hybrid fiber-reinforced composite plate, cylindrical shell, and pressure vessel problems. The standard performance metrics for evaluating multi-objective optimization algorithms are used to demonstrate the effectiveness of the proposed algorithm over other popular evolutionary algorithms like Nondominated Sorting Genetic Algorithms (NSGA-II), Pareto Archived Evolutionary Strategy (PAES), micro-GA, and Multi-Objective Particle Swarm Optimization (MOPSO).
