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Sequencing algorithm with multiple-input genetic operators: Application to disaster resilience

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Abstract

A novel evolutionary optimization methodology called ‘‘Algorithm with Multiple-Input Genetic Operators” (AMIGO) for scheduling independent tasks considering resource and time constraints is presented. AMIGO is characterized by new genetic operators enriched with complementary information, including auxiliary variables computed by the fitness function, as well as the global parameters of the problem. The application of AMIGO to multi-phase optimal resilience restoration scheduling of highway bridges is presented and discussed. To this purpose, enhancements have been made also to the bridge network resilience analysis (a new performance metric and restoration model). The quality of the solution and efficiency of AMIGO are demonstrated through the application to a large transportation network subjected to earthquake.

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... However, this method is highly dependent on accurate origin-destination (OD) flow demand and route choice assumptions based on traffic equilibrium (Chang et al. 2012). During the emergency phase after a major earthquake, the travel behaviour is extremely complex as it is influenced by socioeconomic factors as well as emergency policies, and the choice of drivers may not be rational (Karamlou and Bocchini 2016). Therefore, it is almost impossible to predict the OD flow demand under such high uncertainty (Khademi et al. 2015;. ...
... However, these performance metrics only focus on the impact of network disruptions under normal traffic demand, without considering the possible changes in travel behaviour after disasters. A significant characteristic of the post-disaster emergency phase is the dramatic change of traffic demand (Karamlou and Bocchini 2016;Feng, Li, and Ellingwood 2020;Chang et al., 2010), in which the travel behaviours related to emergency rescue are the most concerned. Franchin, Lupoi, and Pinto (2006) conducted a reliability analysis of the post-earthquake functionality of the road network in terms of the accessibility between schools and hospitals, which takes into account the damage of buildings and road network. ...
... However, this is obviously not in line with reality, but very few studies have considered the issue. Karamlou and Bocchini (2016) defined the network performance metric in emergency response as weighted number of connected OD pairs that are considered urgent. In the metric, the connectivity of OD pairs is divided into three levels (1.0 for fully connected, 0.5 for partially connected, and 0 for disconnected) based on the presence or absence of a fully or partially served route between them. ...
Article
As one of the most important urban infrastructure systems, the road network plays a vital role in post-earthquake emergency response. Quantitative evaluation of the emergency response functionality of road network under earthquakes can provide decision support for emergency planning and future construction. In this paper, a novel network performance metric is proposed to consider both the special traffic demand in emergency response and the supply capability of road network. On this basis, an integrated probabilistic assessment framework for post-earthquake network emergency response functionality is presented, considering various uncertainties. In the framework, a penalty-based approach is proposed to consider the impact of partially degraded links on network functionality. At last, the proposed methodology is illustrated on the road network of Tangshan city, China, under different seismic scenarios.
... Alternatively, the restoration sequence can be simulated with quantitative computational models. For example, the decision on restoration sequencing can be simulated as the solution of an optimization model (Bocchini & Frangopol, 2012a;Chang, 2003;Fang, Fang, Zio, & Xie, 2019;Gonz alez, Dueñas-Osorio, S anchez-Silva, & Medaglia, 2016;Karamlou & Bocchini, 2016;Miles, 2018;Zhang, Wang, & Nicholson, 2017). However, the modeling and solution of optimization problems require the implementation of complicated mathematical formulations and become computationally expensive for large and complex applications, which may render this approach inappropriate for some practitioners. ...
... Practical recovery plans may have different goals (such as minimal repair cost) and conflicting goals (such as minimal life-cycle cost and maximum resilience). The first problem can be addressed by using optimization formulations with a different objective function; the second problem can be addressed by multiple objective optimization methods, such as multi-objective genetic algorithms (Bocchini & Frangopol, 2012b;Karamlou & Bocchini, 2016) and the weighted sum method (Bueno, Haeser, & Mart ınez, 2016;Zhang et al., 2017). ...
... The functionality of an infrastructure system can be defined by different metrics, such as network connectivity (Bocchini & Frangopol, 2013), network flow (Bocchini & Frangopol, 2012b;Ma et al., 2019), and the percentage of customers with service (Mitsova, Escaleras, Sapat, Esnard, & Lamadrid, 2018;Ouyang & Dueñas-Osorio, 2014). This study uses the following metric based on a weighted network (Karamlou & Bocchini, 2016): ...
Article
Due to continuous population expansion and the threat of climate change, the past century has witnessed increasing occurrences of natural hazards, leading to significant global losses and requiring substantial restoration efforts. This issue challenges decision makers to act in a timely and effective manner to protect infrastructure systems from future natural hazards. This study presents a policy-based decision model for restoration planning, as part of the PRAISys platform, to support informed disaster mitigation of interdependent infrastructure systems under uncertainty. Following the concept of disaster recovery priority used in practice, this model determines the priority rank of each recovery task from pre-defined policies and simulates the restoration accordingly. This model captures different types of interdependencies with rigorous models at the component and system levels and predicts possible system recoveries under a given damage scenario in a probabilistic manner. This model can quantitatively evaluate the effectiveness of decision strategies on system recovery and resilience under different disaster recovery policies. As a demonstration example, this study applies the proposed model to the post-earthquake recovery simulation of three interdependent infrastructure systems (i.e., power, communication, and transportation) in the Lehigh Valley, Pennsylvania, USA. A total of sixteen cases were considered to represent different restoration strategies. For every case, the uncertainties in the recovery steps are captured by probabilistic simulation, and system resilience is calculated for every recovery sample. Simulation results from different strategies are compared to evaluate the effectiveness of non-intuitive strategies on system recovery and resilience. The proposed model uses a simple and straightforward concept to mimic practical disaster recovery plans. It is easy to understand and implement for modelers, and it is also useful to compare outcomes from different recovery criteria and decision strategies for practitioners.
... These factors collectively highlight the need for proactive resilience assessment in order to prepare for and mitigate the impacts of various challenges on societal and organizational systems. While resilience analysis has been widely applied in the field of infrastructure [45][46][47][48][49], the resilience of cut slopes on expressways has not been thoroughly studied. ...
... They also proposed a post-disaster recovery curve based on the motion equation of a linear damped oscillator [47]. Karamlou et al. [48] introduced a method to fit the disaster recovery curve for bridges using the cumulative probability function of a normal distribution. Huang et al. [49] derived an accurate post-disaster recovery curve for tunnels based on time-varying convergence performance data. ...
Article
This research evaluates the stability of cut slopes, considering the effects of weathering and the angle of stratification. Incorporating both a weathering degree index and a factor of safety, we developed a novel formula to assess the temporal deterioration of cut slopes. Utilizing this formula, logistic regression was conducted to ascertain cut slope stability. We used the Hierarchical Bayesian model to refine the parameters of the logistic regression function, culminating in the formulation of a comprehensive slope stability probability prediction model. The model’s predicted stability probabilities for diverse cut slopes exhibited a compelling congruence with empirical data upon validation. Importantly, this approach provides expressway management authorities with a tool to preliminarily assess whether longstanding in-service cut slopes require intervention or stabilization measures.
... These factors collectively highlight the need for proactive resilience assessment in order to prepare for and mitigate the impacts of various challenges on societal and organizational systems. While resilience analysis has been widely applied in the field of infrastructure [45][46][47][48][49], the resilience of cut slopes on expressways has not been thoroughly studied. ...
... They also proposed a post-disaster recovery curve based on the motion equation of a linear damped oscillator [47]. Karamlou et al. [48] introduced a method to fit the disaster recovery curve for bridges using the cumulative probability function of a normal distribution. Huang et al. [49] derived an accurate post-disaster recovery curve for tunnels based on time-varying convergence performance data. ...
... Bouzidi, Fies, Faron-Zucker, et al. (2012) developed a rule check to assess the technical guidelines for tile roof installation. Automated systems are considered an appropriate technique when the conditions being assessed are global parameters, such as rules associated with structural integrity, safety, and resilience (Eastman, Lee, Jeong, et al., 2009;Karamlou & Bocchini, 2016). Yet, automated resilience evaluation frameworks have been overlooked in the literature. ...
... The rule checking system was developed as an alternative to this evaluation approach. Automated rule checking is considered an appropriate technique when the conditions being assessed are global parameters, such as rules associated with structural integrity, safety, and (Chen, Buylova, Chand, et al., 2020;Kammouh, Gardoni, & Cimellaro, 2020;Matsuki, 2012) 3 Geographical positioning 3.1 Topographic position index √ (Mosavi, Shirzadi, Choubin, et al., 2020;Munyai, Chikoore, Musyoki, et al., 2021;Song, Huang, & Li, 2017;Wu, Chen, Cheng, et al., 2021;Zhang, Song, Peng, et al., 2019) 3.2 Slope √ (Mosavi, Shirzadi, Choubin, et al., 2020;Song, Huang, & Li, 2017;Wu, Chen, Cheng, et al., 2021;Zhang, Song, Peng, et al., 2019) 3 resilience (Eastman, Lee, Jeong, et al., 2009;Karamlou & Bocchini, 2016). Due to the benefits of automation, rule checking systems have recently gained the attention of researchers and practitioners. ...
Article
Residential infrastructure, particularly multi-unit residential buildings (MURBs), lacks sufficient attention to resilience. This oversight is attributed to the absence of specific guidelines for assessing MURBs’ resilience, with existing literature primarily concentrating on singular hazards. Additionally, current frameworks for resilience evaluation necessitate manual interpretation, leading to time and cost inefficiencies and potential human errors. The present study, therefore, developed a comprehensive framework and an automatic rule-based checking system on MURB resilience that can be utilized as a decision support system for practitioners. A literature review revealed 44 resilience indicators, categorized into four based on the general characteristics, i.e., technical, organizational, geographical positioning, and economic. The resilience indicators were benchmarked and defined as a building information modeling (BIM) ruleset. A case study was conducted to demonstrate the execution of the developed BIM ruleset using a MURB design. The proposed framework and rule-based checking system help ensure that MURBs comply with resilience requirements.
... In the context of freight transportation networks, resilience is typically evaluated by integrating network functionality QðtÞ at time t over the duration of recovery (Reed et al. 2009;Karamlou and Bocchini 2016). Alternatively, the integration of functionality over time is normalized by a target preevent functionality level Q T ðtÞ in the definition of resilience (Ouyang and Wang 2015), as shown in Eq. (1) ...
... The resulting models are used to quantify resilience based on user-defined metrics of connectivity, travel time, travel cost, or value of freight transported. Intermodal network Ratio of expected postevent network demand to preevent demand Omer et al. (2011) Road network Ratio of postevent travel time to preevent travel time Faturechi and Miller-Hooks (2014) Road network Ratio of postevent travel time to preevent travel time Karamlou and Bocchini (2016) Road network Connectivity measure Chen et al. (2017) Intermodal network Adaptation of Miller-Hooks' metric to quantify connectivity, travel time, and capacity Guidotti et al. (2017) Bridge network Network efficiency Zhang et al. (2017) Road network Same as Ip andWang (2011) Ganin et al. (2019) Road network Total delay in travel time ...
Article
This study introduces a framework for quantifying the time-evolving functionality and, consequently, the resilience of rail-truck intermodal freight transportation networks subjected to regional disruptions from events like natural hazards. The proposed framework leverages publicly available datasets and probabilistic models for estimating the damage and functionality of the components of the intermodal network. New restoration models linking physical damage to functionality have been proposed in this study, improving upon previous literature in this area. Furthermore, the framework for quantifying the resilience of intermodal networks is posed to consider not only the functionality of constituent highway and railway networks and their components but also that of intermodal terminals in its formulation. The framework enables the estimation of network throughput and functionality metrics at various instances during the recovery timeline and can be extended to assess the broader economic impacts of freight disruption on the community.
... Under a hazard scenario, both nodes and links are subject to failure, with binary functionality (ATC 1985;Guidotti et al. 2017;Sun et al. 2020b), continuous functionality (Karamlou and Bocchini 2017b;Thurner et al. 2018), or discrete functionality (Shinozuka et al. 2003;Bocchini and Frangopol 2011a;Karamlou and Bocchini 2017a). The system functionality is usually defined based on the network topology or network flow, such as connectivity (Dueñas-Osorio and Vemuru 2009; Bocchini and Frangopol 2011b), number of functional/failed/repaired components (Johansson and Hassel 2010;Karamlou and Bocchini 2016), flow capacity Frangopol 2011b, 2012a, b), number of customers with service (Mitsova et al. 2018;Sun et al. 2020b, c), and network flow (Lee et al. 2007;Ma et al. 2019). In addition to physical dependencies, the link concept can be generalized to describe other types of dependencies across systems, and a joint adjacency matrix can be used to describe both physical connectivity and other dependencies. ...
... Functionality dependencies, including both compositional functionality dependencies and intersystem functionality dependencies, can be represented by rigorous restoration functions (Karamlou and Bocchini 2017a;Sun et al. 2019Sun et al. , 2020bLiu et al. 2021). In applications of dependencies and interdependencies, optimization models are often integrated with other models, such as network models (Karamlou and Bocchini 2016;Ouyang 2017;Zlotnik et al. 2017;Almoghathawi et al. 2019;Ma et al. 2019;Karakoc et al. 2019) and agent-based models (Permann 2007;Kizhakkedath et al. 2013). For instance, optimization models have been applied to identifying effective recovery decisions on network resilience enhancement (Vugrin et al. 2014;Ouyang and Wang 2015;Zhang et al. 2018;Sun et al. 2020b). ...
Article
Critical infrastructure systems are interdependent to ensure normal operations for supporting a national economy and social well-being. In the wake of a disaster, such interdependencies may introduce additional vulnerability and cause cascading failures. Therefore, understanding interdependencies and assessing their impact are essential to mitigate such adverse consequences and to enhance disaster resilience in the long term. There have been various models developed to capture dependencies and interdependencies across infrastructure systems. However, problems of inconsistent usage and a lack of technical guidance hinder practical applications of interdependency models. Therefore, this study presents a new classification of interdependency models based on the following implementation methods: dependency tables, interaction rules, and data-driven approaches. For every class of interdependency model, fundamental assumptions and detailed implementation methods are described, with discussion of appropriate application areas, advantages, and limitations. This study also compares different types of models to facilitate analysts in choosing models based on their needs. Due to the intrinsic complexity of dependencies and interdependencies, there are many challenging modeling issues; this study discusses future research directions to address such challenges.
... Appropriate traffic assignment and distribution techniques are adopted to handle traffic demand in the system before and after the seismic event. Adopting the same methodology and concept, Karamlou and Bocchini (2016) evaluated resilience of a real highway network in San Diago, CA that constitutes 80 bridges. The primary objective of that study was to develop a robust optimisation algorithm named Algorithm with Multiple-Input Genetic Operators, which was further applied to identify resilience-based optimal postearthquake restoration interventions of damaged highway bridges. ...
... It is assumed that the time taken for restoration has linear dependency on the damage level of bridges. Other studies related to seismic resilience of bridge networks used the recovery model proposed in HAZUS (HAZUS-MH 2004) with or without case-wise customisations (Alipour & Shafei, 2016;Karamlou & Bocchini, 2016). Readers can also refer to Gidaris et al. (2017) for a discussion on available restoration models of highway bridges for the purpose of resilience assessment under earthquake and tsunami hazards. ...
Article
Assessment of resilience for engineered systems has drawn ample attention from the engineering community in recent years. It has resulted in a significantly large body of literature focusing on pertinent areas of resilience. This article provides a systematic and comprehensive review of the literature addressing resilience assessment of bridges and bridge networks under single hazard and multihazard conditions. Though not much work been performed yet on multihazard resilience of bridges, relevant aspects including combinations of multiple hazards for bridge performance evaluation, methods for loss assessment and approaches taken for post-event recovery are discussed. Furthermore, maintenance is a key component if resilience is assessed in a life-cycle framework. Hence, available maintenance plans and strategies and their probable applications for bridges and bridge networks are discussed. The article concludes with a discussion on the need for further research in the focus area and challenges involved with the same. ARTICLE HISTORY
... Appropriate traffic assignment and distribution techniques are adopted to handle traffic demand in the system before and after the seismic event. Adopting the same methodology and concept, Karamlou and Bocchini (2016) evaluated resilience of a real highway network in San Diago, CA that constitutes 80 bridges. The primary objective of that study was to develop a robust optimisation algorithm named Algorithm with Multiple-Input Genetic Operators, which was further applied to identify resilience-based optimal postearthquake restoration interventions of damaged highway bridges. ...
... It is assumed that the time taken for restoration has linear dependency on the damage level of bridges. Other studies related to seismic resilience of bridge networks used the recovery model proposed in HAZUS (HAZUS-MH 2004) with or without case-wise customisations (Alipour & Shafei, 2016;Karamlou & Bocchini, 2016). Readers can also refer to Gidaris et al. (2017) for a discussion on available restoration models of highway bridges for the purpose of resilience assessment under earthquake and tsunami hazards. ...
Article
Assessment of resilience for engineered systems has drawn ample attention from the engineering community in recent years. It has resulted in a significantly large body of literature focusing on pertinent areas of resilience. This article provides a systematic and comprehensive review of the literature addressing resilience assessment of bridges and bridge networks under single hazard and multihazard conditions. Though not much work been performed yet on multihazard resilience of bridges, relevant aspects including combinations of multiple hazards for bridge performance evaluation, methods for loss assessment and approaches taken for post-event recovery are discussed. Furthermore, maintenance is a key component if resilience is assessed in a life-cycle framework. Hence, available maintenance plans and strategies and their probable applications for bridges and bridge networks are discussed. The article concludes with a discussion on the need for further research in the focus area and challenges involved with the same.
... Eqs. (3)(4)(5) consider the fatigue factor of the maintenance team in repairing faulty nodes, which indicates that as the maintenance work progresses, the crew could feel tired and extend the task processing time. ...
Preprint
Full-text available
Power networks are highly vulnerable to disruptions caused by natural and man-made disasters, necessitating prompt restoration of damaged power supply. This research addresses the challenge of efficiently restoring large-scale power networks, which often involve numerous unknown or uninspected faulty nodes. Leveraging advancements in unmanned aerial vehicles (UAVs) technology, this study facilitates the inspection of these nodes and subsequent manual maintenance. However, coordinating maintenance teams and UAVs is complex due to the intricate network structure and scheduling correlations. We propose a learning-driven (LD) algorithm to enhance human-UAV collaboration for effective power network restoration. The algorithm includes an initialization method to generate promising initial solutions, followed by the use of search operators as basic action elements and a learning engine to guide search directions based on state assessments. Comprehensive experiments validate the algorithm’s effectiveness in improving the restoration process.
... Therefore, a novel GA is developed for solving the bilevel programming model. Previous research has shown that the GA can produce high-quality results for restoration scheduling problems [1,24,37]. The pseudocode for the proposed GA for the restoration scheduling problem is illustrated in Table 2. ...
Article
Full-text available
Disruptive events cause decreased functionality of transportation infrastructures and enormous financial losses. An effective way to reduce the effects of negative consequences is to establish an optimal restoration plan, which is recognized as a method for resilience enhancement and risk reduction in the transportation system. This study takes the total travel time as the resilience measure to formulate a bilevel optimization model for a given scenario. However, the uncertainties involved in restoration activities cannot be overlooked. In this context, the inherent uncertainty is represented with a set of scenarios generated via the Latin hypercube technique. To assess the risk under uncertainty, a conditional value at risk with regret (CVaR-R) measure is introduced when considering the existence of worst-case scenarios. Then, the bilevel programming model is transformed from the deterministic case to the stochastic case, where the upper-level problem determines the restoration sequence to minimize CVaR-R and the lower-level problem is a traffic assignment problem. An integrated framework based on a novel genetic algorithm and the Frank—Wolfe algorithm is designed to solve the stochastic model. Numerical experiments are conducted to demonstrate the properties of the proposed bilevel programming model and the performance of the solution algorithm. The proposed methodology provides new insights into the restoration optimization problem, which provides a reference for emergency decision-making.
... .47%,22.49%, 34.16%, and 38.99% at25,50,75, and 100 years, respectively, compared to the initial state. This indicates significant degradation in shear capacity, particularly in splash and tidal zones, which become vulnerable areas for pier shear performance. ...
Article
Full-text available
A comprehensive probabilistic assessment framework and methodology for evaluating the seismic resilience of in-service bridge structures have been developed, utilizing a combination of the maximum drift ratio (MDR) and residual drift ratio (RDR) indicators. This approach effectively addresses non-uniform corrosion on structural facades and the consequential shift in failure modes due to corrosive damage. To illustrate its applicability, a seismic resilience analysis was conducted over the life-cycle of a RC bridge. Based on the time-varying seismic fragility analysis, a further assessment was conducted, which encompassed post-earthquake functional loss, the recovery process, and seismic resilience. The research findings emphasize that corrosive damage significantly diminishes the seismic performance of bridge piers. As the service life progresses, both MDR and RDR gradually increase, demonstrating a positive correlation. Damage probabilities and functional losses obtained through the MDR-RDR indicators exceed those derived from single indicators. Additionally, the functional recovery time based on MDR-RDR indicators consistently exhibits an escalation. As service life and PGA levels increase, the seismic resilience assessed using various indicators displays a declining trend, with a particularly notable reduction rate observed for the MDR-RDR indicator. The results of this study underscore the importance of concurrently considering aging and combined indicators when assessing the seismic resilience of bridge structures throughout their service life. These results provide novel insights for the comprehensive assessment of seismic resilience in structures during service period.
... Several studies have topologically assessed the emergency road network connectivity and identified vulnerable points (Kozawa, Nakayama, et al., 2021;Zhang, Wang, et al., 2017). Not only emergency but ordinary road networks, including the connectivity of bridges, are being examined (Akbarzadeh, Memarmontazerin, et al., 2019;Bhatia, Sela, et al., 2020;Karamlou and Bocchini, 2016;Liu and Frangopol, 2005b;Testa, Furtado, et al., 2015;Zhang and Wang, 2016). ...
Article
Full-text available
Due to budget constraints in the local cities of Japan, there is an urgent need to prioritize the maintenance or removal of aging transportation infrastructure, particularly bridges. Given the declining tax revenues, our study proposes an approach to systematically address this challenge. Using GIS network analysis, we evaluated the impact of bridge removal on the daily travel time of residents, considering the intricate road network and population distribution of the selected study area, Island A. Various public facilities on the island were identified as potential destinations. Our methodology assessed the changes in travel time for residents if a bridge was removed. Four distinct bridge removal scenarios were proposed: two prioritize minimal disruption in resident travel time, and the other two focus on the life-cycle costs (LCC) of the bridges. This analytical process aims to achieve a balance between fiscal responsibility and ensuring resident convenience. By proposing efficient bridge removal plans based on the consequences of each scenario, we hope to guide local governments in making informed decisions. Through this Japanese case study, our methodology offers valuable insights into formulating strategies for other developed areas facing similar infrastructure challenges.
... Post-disaster decision-making on recovery management is one of the most promising fields for the application of resilience in engineering practice [23] . Frangopol and Bocchini proposed an optimization model for the post-disaster restoration schedule of transportation networks with respect to the total present cost, using both the total travel time (TTT) and total travel distance (TTD) as network performance metrics [24] . In addition to long-term resilience indicators, Karamlou and Bocchini introduced a connectivity-based resilience indicator to optimize the restoration priorities during medium-phase disaster management [25] . ...
Article
Full-text available
The road transportation infrastructure system (RTIS) provides a network of options that support the movement of people and goods. As a critical lifeline system, the resilience assessment of RTISs under the impact of different natural hazards, particularly earthquakes, has attracted extensive attention. When an earthquake occurs, an assessment of the connectivity reliability and travel time on road networks is necessary for emergency planning. In this study, the road network in the Aba Autonomous Prefecture, Sichuan Province, China, was considered as the study area and divided into 13 traffic analysis zones (TAZs) based on the administrative divisions. To consider the uncertainties related to seismic hazard assessment, random fields of ground motions were generated using a Monte Carlo simulation (MCS), considering the spatial correlation. Additionally, a connectivity reliability assessment model and travel time assessment model for the road networks were proposed. The connectivity reliability between the TAZs and increased travel time on the road networks after an earthquake were evaluated using MCS to evaluate the uncertainties related to the damage state assessment of road assets, such as bridges, tunnels, and road segments. Consequently, the results can be used as a theoretical basis for decision-making on the location and number of emergency rescue points after an earthquake and as a functional metric for resilience assessment models.
... Ikpong and Bagchi (2015), Minaie and Moon (2017), and Stevens and Tuchscherer (2020) developed an index to evaluate the bridge resilience against climate-change-related multihazard events. Karamlou and Bocchini (2016), Domaneschi and Martinelli (2016), Andrićand Lu (2017), and Ghasemi and Lee (2021a) developed a matrix to measure the seismic resilience of bridges. Patel et al. (2020) and Mitoulis et al. (2021) presented a framework to compute bridge resilience against floods. ...
... The second way is based on contemporary computational and mathematical techniques and capabilities that allow to simulate and optimize the recovery process. In this case, the recovery process is viewed as a set of actions that must be carried out by a group of agents and stakeholders, and the corresponding restoration plan is generated by matching actions and agents using linear programming [3] or more complex techniques like a genetic algorithm [4,5,6]. An optimization approach's restriction is the requirement for correct information or at least the proper estimation [7] of the status of the damaged system and the evaluated state to which the city must be restored. ...
Article
Full-text available
Present work is devoted to the problem of emergency response to a large-scale disaster and the recovery management of an urban socio-technical system. An iterative algorithm based on reactive decision-making is proposed as an approach enabling the recovery manager to test a set of potential restoration priorities using numerical simulation and agent-based modeling. The proposed method helps to coordinate reconstruction processes even in the case when the information is fluid and uncertain via providing a set of different recovery plans, the efficiency of which may be assessed using various factors. It also enables to determine how an under- or over-evaluation of the damage degree will affect the integral duration of the recovery process. As a result, the recovery manager will be supplied with a collection of possible recovery plans, which are numerically tested, visualized, and whose relative efficiency is evaluated using multiple estimators. Such an outcome enables to avoid the delay of recovery initiation caused by the ambiguity of the initial state of the system and the impossibility to define the recovery strategy right after a disaster occurrence.
... In the post-earthquake chaotic environment, the transportation network is considered as one of the most significant infrastructure systems to support emergency response activities, and the disruption of transportation networks could lead to additional casualties, economic losses and secondary disasters [43,[68][69][70][71]. Maintaining effective connectivity between affected areas and the emergency facilities has always been recognized as the immediate priority following a major earthquake [40,[72][73][74]. In this paper, we utilize an improved connectivity-based model to evaluate the post-earthquake network functionality of emergency response [75]. ...
Article
Full-text available
Seismic mitigation of transportation systems has become a worldwide challenge, because identifying an optimal retrofit strategy entails significant computational efforts, especially for large-scale networks with numerous candidate strategies and time-consuming risk assessment processes. An efficient joint importance-based methodology is proposed in this paper to address the challenge. The proposed method selects the component set (e.g., bridges) that is most decisive to the network seismic risk based on only one set of stochastic samples but takes into account the uncertainty of multiple damage states and the interactive effect between different components. The reliability and stability of the proposed method are verified on a hypothetical transportation network under different conditions.
... In other cases, nodes and links may have continuous or discrete functionality states, ranging between 0 and 100% (Bocchini and Frangopol 2011;Cimellaro et al. 2015;Guidotti et al. 2016;Manzo et al. 2012;Shinozuka et al. 2003aShinozuka et al. , 2003b. The system functionality is usually defined based on the network topology and/or network flow, in terms of connectivity loss (Dueñas-Osorio et al. 2007;Bocchini and Frangopol 2013), number of functional or failed or repaired components (Di Muro et al. 2016;Johansson and Hassel 2010;Karamlou et al. 2016), the reciprocal shortest path length (Ouyang et al. 2009), flow capacity (Bocchini and Frangopol 2011a, 2012a, 2012b, or number of customers with or without service (Poljanšek et al. 2012). In addition, network flow can be used as the functionality metric to assess the impact of interdependencies on the network functionality by considering the nodal capacity (Lee II et al. 2007;Wallace et al. 2003). ...
Chapter
Full-text available
Critical infrastructure systems provide essential services for economic prosperity and a good quality of life. Over time, they have become increasingly interdependent on each other at multiple levels. Under ordinary conditions, these interconnections enhance the overall performance of the infrastructure and can accelerate the transition to “smart cities”. However, in the case of extreme events, interdependencies introduce additional vulnerabilities that can lead to cascading failures and delays in restoration activities. Consequently, better understanding of the interdependencies among critical infrastructure systems and an objective way to model them are important to support planning, design, maintenance, and emergency decision-making, especially if disaster resilience is the ultimate focus. Since resilience is a systemic property, any model that addresses the various infrastructure sectors independently is likely to yield inaccurate predictions. This chapter provides a comprehensive review of available methods to model infrastructure interdependencies for researchers, practitioners, and administrators who are interested in the quantification, prediction, and enhancement of disaster resilience. Current implementations of dependency and interdependency are mainly realized through dependency tables and interaction rules. Within every major implementation category, detailed classifications of modeling methods are described. For each classification, we discuss fundamental assumptions, computational implementation, most suitable areas of application, advantages and limitations. We then review how various computational frameworks and tools implement different interdependency models for community resilience assessments, followed by future directions for research and practice.
... The throughput is presented as an effective measure to assess the rail-based freight transportation system's resilience to disaster events, including floods, earthquakes, and terrorist attacks (Zhang and Miller-Hooks 2015). Similarly, the traffic-carrying capacity in bridge system functionality analysis has been presented in many works (Decò et al. 2013;Dong and Frangopol 2016;Guo et al. 2017;Karamlou and Bocchini 2016;Padgett and DesRoches 2007;Zhang et al. 2017). To define the bridge damage-functionality relationship, the traffic flow functionality model associated with the considered damage states can be expressed through the following form: ...
Article
River-crossing bridges are often subject to multiple hazards, including foundation scour, seismic attacks, and environmental degradation. When river-crossing bridges are in service, they should be restored rapidly after any disruption over their lifetime. To achieve this resilient quality, it is necessary to assess the system resilience subjected to multihazard impacts and the beneficial effects of any retrofitting or hazard-countermeasure in a lifetime context. To river-crossing bridges, one important intervention is to implement scour countermeasures. This study presents a probabilistic framework to quantify the lifetime system resilience of river-crossing bridges subject to multiple hazards. Notably, the framework is designed to reveal how progressive and abrupt hazards interact and result in resilience degradation and how scour countermeasures contribute to resilience enhancement. Experimental outcomes reveal the positive and distinct effects of implementing scour countermeasures at different times. The proposed framework is expected to assist civil engineers in conducting lifecycle management of river-crossing bridges that are subject to hydraulic scour and demand timely countermeasures.
... Similarly, traffic-carrying capacity for bridge system functionality analysis has been presented in many research works(Decò et al., 2013;Dong & Frangopol, 2016;A. Guo et al., 2017;Karamlou & Bocchini, 2016; functionality relationship, the traffic flow functionality model associated with the considered damage states can be expressed through the following form ], ±*) is the post-event time-dependent average daily traffic (ADT) of the link that is usually expressed in discrete-valued tables in literature, variable ranges from 0 to 1, and § : is bridge ADT at the full functionality, and XL ./ is the integrated damage index from Equation (2.15).For example,Shinozuka et al. (2008) assumed 100%, 25%, and 10% link traffic throughput for minor, moderate, and collapse damage states, respectively(Shinozuka et al., 2008). ...
Thesis
Bridge structures are required to possess high reliability and robustness against the concurrent effect of extreme loads and environmental attacks. To achieve such interrelated goals, it is necessary to assess the system performance and resilience subjected to multi-hazard impacts and the beneficial effects of any retrofitting or hazard-countermeasure in a lifecycle context. The damaged bridge needs to be restored rapidly over its service life due to the significant economic losses and disruption to transportation networks. For river-crossing bridges, one of the essential hazard mitigation strategies is scour countermeasures. However, a quantitative understanding of the effects of SCs on bridge system resilience is not found. This dissertation presents a critical synthesis of the existing literature that provides relevant knowledge and a profound understanding of probabilistic multi-hazard assessment for bridge structures. Then, a finite element-based probabilistic framework is designed to assess the lifecycle resilience of reinforced concrete river-crossing bridges under seismic, flood-induced scour, and chloride-induced corrosion impacts, including the consideration of a typical scour countermeasure at variable service times. Based on the general performance-based approach, two probabilistic models are formulated, termed the mean-scour fragility analysis (MS-FA) model and the total-scour demand hazard analysis (TS-DHA) model, which produce straightforward functional curves and can be readily used to evaluate the seismic-scour multi-hazard effects. An integrated damage index is defined based on both local and system-level ductility demands to develop a demand hazard model and to estimate the damage-based residual functionality and recovery duration to quantify the lifecycle bridge resilience. Notably, the exceeding probability approach is designed to reveal how progressive and sudden hazards interact and result in resilience degradation and how scour countermeasures contribute to resilience enhancement. The outcomes of the numerical experiment reveal the positive and distinct effects of implementing SCs at different lifecycle intervals. More importantly, resilience time-series demonstrate arbitrary multi-modes and nonparametric patterns. Accordingly, a robust statistical distance-based approach is presented to determine the sequential evolution of time-varying multi-hazard resilience. The proposed framework would assist stakeholders and decision-makers in resilience patterns recognition, assessing the effectiveness of hazard mitigation strategies, and taking short- and long-term proactive intervention actions by specifying resilience thresholds. Here is the link to download the full-text: https://mospace.umsystem.edu/xmlui/handle/10355/78906
... In addition to the long-term resilience indicator, Karamlou and Bocchini (2016) introduced a connectivity-based resilience indicator to optimise the restoration priorities during mediumphase disaster management. Zhang, Wang, and Nicholson (2017) presented a framework to optimise the restoration schedule for post-earthquake road network based on the total recovery time (TRT) and skew of recovery trajectory (SRT), where the network performance is measured by weighted average number of reliable interdependent routes over all origindestination (OD) pairs. ...
Article
Transportation network is of vital importance for city maintaining and reconstruction especially after extreme events. Decisions on the restoration plan of transportation network have to be made in a short period after event, but taking into account various decision-making criteria and resource constraints. This paper explains the essential problems in network restoration scheduling, and presents a novel resilience-based optimisation model for post-disaster urban transportation network restoration. The proposed method could obtain a set of general optimal restoration schedules in an efficient manner, so that decision-makers could make a final choice by weighting other preferences and experience. In the methodology, a new travel speed-based metric is introduced for performance assessment of transportation network, and three normalised independent indicators are developed to characterise network resilience from the perspective of functionality curve. Furthermore, a bi-objective optimisation model based on the recovery trajectory is recommended to search for non-dominated optimal restoration schedules. To illustrate the proposed method, heuristic algorithms are used to solve the restoration schedule optimisation problem of a hypothetical transportation network.
... The European project SYNER-G provided a computation framework for seismic vulnerability and risk analysis of interdependent civil infrastructure systems, including social losses as a result of direct physical damage to facilities and their lack of functionality (Franchin, 2014;Pitilakis et al., 2014). The National Science Foundation funded project PRAISys focuses on using mathematical techniques to address stochastic interdependencies among infrastructure systems after an extreme event in a probabilistic way (Karamlou & Bocchini, 2016a, 2016b. The NIST funded Center for Risk-Based Community Resilience Planning provides a quantitative and science-based approach to comprehensively assess community resilience by narrowing the gap between engineering, social sciences, and economics (Ellingwood et al., 2016). ...
Article
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... Also, the concept of resilience triangle proposed by Bruneau et al. is one of the most common tools to quantify resilience, and the underlying idea inspired several researchers to propose other metrics and methodologies to measure, enhance, and optimize resilience of different structures and infrastructure systems [6][7][8][9]. These include, but are not limited to, healthcare structures and facilities [10,11], power grids [12,13], gas distribution systems [14], bridges and transportation networks [15][16][17]. As indicated in the definition of resilience, the assessment of the restoration process of different units of the community and their functionality immediately after the event and during the recovery phase are among the key steps of resilience assessment. ...
Conference Paper
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To reduce the negative impacts of indirect losses after an extreme event, typically caused by long-lasting reduced functionality of critical structures and infrastructure systems, disaster managers need to plan the disaster relief activities considering the post-event resilience as one of the main determining factors. However, this requires better understanding of the restoration process of the system and the underlying uncertainties, as well as the impact of each component on the functionality of the system. In this paper, a technique is presented to simulate the restoration schedule and recovery curve of damaged infrastructure systems with multiple components. This is carried out by assembling the restoration tasks of each damaged component of the system considering the availability of resources for the restoration activities, and the uncertainties involved in restoration duration. The application of the proposed methodology is presented for two cases: an electrical distribution substation, and a pair of bridges, all with multiple damaged components. Sample restoration schedules and recovery curves are presented, and probabilistic restoration functions are derived for every structure.
... The concept of resilience has been studied in a large number of fields such as engineering, psychology, sociology, ecology, business, and economics. In the engineering world, resilience has been generally defined as the ability and capacity of a system or social units to absorb, withstand, and efficiently recover from a perturbation to an acceptable level of functioning [1]. It is a characteristic of the system that indicates performance under unusual conditions, recovery speed, and the amount of outside assistance required for restoration to its original functional state [2]. ...
Chapter
Risk-informed life-cycle engineering provides a viable approach for addressing the challenges posed by climate change for developing appropriate design and management criteria for structures and infrastructure systems. The basic mathematical formulations are first presented and followed by a discussion of important factors that must be considered during the life-cycle analysis of structures and infrastructure systems. The input for the time-variant reliability analysis consists of probabilistic models for climatic loads and member capacities both of which are affected by changes in weather patterns. The chapter reviews the following topics that constitute important components of climate-focused life-cycle engineering: infrastructure interdependencies and multi-hazard effects under climate change; and effective optimization techniques for life-cycle management of new and existing structures in a changing climate. It also reviews strategies for infrastructure management subject to climate change illustrated through the management of transportation systems as an example case.
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This study underscores the critical need to integrate changing climatic conditions into corrosion models for civil engineering infrastructures, particularly highway bridges, given the potential reduction in structural performance post-seismic events. The paper introduces a novel framework for assessing the seismic resilience of deteriorated highway bridges in the context of changing climatic conditions. The framework is demonstrated on a non-seismically designed simply supported highway bridge situated near the sea in a seismically active region of Gujarat, India. An improved corrosion deterioration model is used that considers the impact of climate change and non-uniform pitting corrosion for evaluating the deterioration of RC bridge components. A detailed three-dimensional finite-element model of the case-study bridge is developed that can accurately simulate various failure modes of corroding bridge piers. Time-varying seismic fragility curves are developed using damage limit states and probabilistic seismic demand models while considering the influence of climate change. Bridge seismic resilience is estimated by aggregating the seismic vulnerability, losses, and recovery functions. Results show that incorporation of changing climatic factors will considerably reduce the seismic resilience of the 75-year corroded bridge up to 56 %. Finally, a comparison of seismic fragility and resilience is carried out using the proposed and conventional corrosion deterioration model to evaluate the significance of considering the effects of climate change in the seismic resilience assessment framework.
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Conference Paper
The impact of climate change due to increasing global warming may negatively influence the performance of reinforced concrete (RC) bridges. In addition to being continuously exposed to unfavorable climatic conditions, bridges in India are also prone to earthquake-induced damage. This study provides a methodology for time-dependent seismic resilience assessment of aging highway bridges considering climate change effects. Nonlinear time-history analyses are conducted to develop seismic fragility curves at different points in time. These results are utilized to estimate seismic losses that are combined with recovery models to estimate the functionality and resilience of aging highway bridge considering climate change effects. The results reveal a declining trend in the resilience of the bridge after taking climate change into account, underlining the significance of considering climate change when evaluating the lifetime seismic resilience of older bridges.
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The resilience of a bridge is computed using different quantitative and qualitative assessment methodologies. However, the resilience score obtained by these assessment approaches is insufficient for the decision-makers for setting a priority level for bridges in need of resilience improvement. To address this issue, the present study develops a methodology using the data envelopment analysis (DEA) approach. A total of 12 bridges are selected as the decision-making units in the DEA model. This study considers the variables such as age, area, design high flood level, and finish road level of the bridge as inputs, and bridge resilience index as the output variable. Based on these variables, three frameworks are developed to compute the efficiency of bridge resilience. A variable return to scale with the output-oriented formulation of DEA is selected to compute the efficiency of bridge resilience in all three frameworks. Thus, the proposed methodology enables bridge owners to set a priority level for bridges in need of resilience improvement based on the scores of the assessment methodology.
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Infrastructure interdependencies have been widely recognized, especially in the postdisaster restoration process. It is essential to develop models to simulate interdependencies and quantify their impact on the functionality recovery of infrastructures. This study presents a generalized simulator to investigate the impact of different types of interdependency on functionality recovery. The proposed simulator considers that there are multiple possible modes to execute a restoration task by framing the restoration process of interconnected systems as a multimode resource-constrained project scheduling problem (MRCPSP). In addition, it considers three sets of uncertainties: restoration duration and resource demand to execute a task, as well as intersystem functionality dependency. By solving the MRCPSP with the objective of minimal restoration completion time, the optimal restoration schedules for different systems are calculated to predict functionality recovery. This simulator implements three types of interdependencies at both the component level and the system level: resource-sharing interdependency, restoration precedence dependency, and functionality dependency. Through a simple example, it is demonstrated how the proposed approach can quantitatively evaluate the impact on system recovery due to different types of interdependency. Research findings from this study can help to identify the interdependencies with the strongest impact and then develop preventive mitigation actions and effective plans of emergency response and disaster recovery for interconnected systems.
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Critical infrastructure resilience has become a national priority for the US Department of Homeland Security. Rapid and efficient restoration of service in damaged transportation networks is a key area of focus. The intent of this paper is to formulate a bi-level optimisation model for network recovery and to demonstrate a solution approach for that optimisation model. The lower-level problem involves solving for network flows, while the upper-level problem identifies the optimal recovery modes and sequences, using tools from the literature on multi-mode project scheduling problems. Application and advantages of this method are demonstrated through two examples.
Article
Computer Science and Operations Research continue to have a synergistic relationship and this book represents the results of the cross-fertilization between OR/MS and CS/AI. It is this interface of OR/CS that makes possible advances that could not have been achieved in isolation. Taken collectively, these articles are indicative of the state of the art in the interface between OR/MS and CS/AI and of the high-caliber research being conducted by members of the INFORMS Computing Society.
Article
This paper proposes a new multi-stage framework to analyze infrastructure resilience. For each stage, a series of resilience-based improvement strategies are highlighted and appropriate correlates of resilience identified, to then be combined for establishing an expected annual resilience metric adequate for both single hazards and concurrent multiple hazard types. Taking the power transmission grid in Harris County, Texas, USA, as a case study, this paper compares an original power grid model with several hypothetical resilience-improved models to quantify their effectiveness at different stages of their response evolution to random hazards and hurricane hazards. Results show that the expected annual resilience is mainly compromised by random hazards due to their higher frequency of occurrence relative to hurricane hazards. In addition, under limited resources, recovery sequences play a crucial role in resilience improvement, while under sufficient availability of resources, deploying redundancy, hardening critical components and ensuring rapid recovery are all effective responses regardless of their ordering. The expected annual resilience of the power grid with all three stage improvements increases 0.034% compared to the original grid. Although the improvement is small in absolute magnitude due to the high reliability of real power grids, it can still save millions of dollars per year as assessed by energy experts. This framework can provide insights to design, maintain, and retrofit resilient infrastructure systems in practice.
Article
This paper presents an optimization procedure for the restoration activities associated with the bridges of a transportation network severely damaged by an earthquake. The design variables are (i) the time intervals between the occurrence of the distress and the start of the interventions on each bridge of the network; and (ii) the restoration pace of the interventions, which represents a measure of the funding allocated to each bridge. The objectives of the optimization are the maximization of the network resilience, the minimization of the time required to reach a target functionality level, and the minimization of the total cost of the restoration activities. Because the first two objectives clearly conflict with the last one, the optimization procedure does not provide a unique solution, but an entire set of Pareto solutions. A numerical example involving a complex, existing transportation network in Santa Barbara, California, illustrates the capabilities of the proposed methodology. [DOI: 10.1193/1.4000019]
Article
In this paper, a general framework for the optimal resilience- and cost-based prioritization of interventions on bridges distributed along a highway connection between two cities that have experienced a disruptive natural or man-made event is proposed. Given the structural damage levels after the extreme event and the bridge characteristics, the proposed computational procedure finds the best intervention schedules, defined as starting time and progress pace of the restoration. The possible intervention schedules are considered optimal when they maximize the resilience of the highway segment and minimize the total cost of interventions. Because the two objectives are conflicting, the procedure uses genetic algorithms (GAs) to automatically generate a Pareto front of optimal solutions. Numerical examples are presented and discussed. DOI: 10.1061/(ASCE)BE.1943-5592.0000201. (C) 2012 American Society of Civil Engineers.
Article
This paper addresses the issue of connectivity-and cost-based optimal scheduling for maintenance of bridges at the transportation network level. Previous studies in the same field have considered the connectivity just between two points or other network performance indicators, such as the total travel time. In this paper, the maximization of the total network connectivity is chosen as the objective of the optimization, together with the minimization of the total maintenance cost. From a computational point of view, several numerical tools are combined to achieve efficiency and applicability to real cases. Random field theory and numerical models for the time-dependent structural reliability are used to handle the uncertainties involved in the problem. Latin hypercube sampling is used to keep the computational effort feasible for practical applications. Genetic algorithms are used to solve the optimization problem. Numerical applications to bridge networks illustrate the characteristics of the procedure and its applicability to realistic scenarios.
Article
The large losses occurred in the past due to earthquakes, even in highly developed countries, as well as the ensuing prolonged inactivity of the stricken societies, imparted momentum to research into regional seismic impact and community resilience to earthquakes. Need for comprehensive and consistent modeling is apparent, and this work presents a contribution in this direction. The extension of a recently developed civil infrastructure simulation framework to the evaluation of resilience, as well as the introduction of a new infrastructure network-based resilience metric represent the novelties of the article and allow one to explore the effect that sources of uncertainty and key vulnerability factors have on the probability distribution of resilience.
Article
Given the importance of encouraging residents of a disaster-stricken community to remain there during the recovery process, this paper examines the determinants of disaster evacuee decisions to return to their communities, and if they return, to stay in the community where they lived before the disaster. The data come from two panel surveys of Hurricane Katrina survivors. The surveys were taken in 2005, just after Katrina, and again in 2006, a year after the disaster. Although the study sample is not indicative of the pre-Katrina population of New Orleans, it is of great value in allowing us to understand the behaviors of disaster survivors and in helping to design disaster recovery plans. Analytical results show that government performance in initial disaster recovery and individual perceptions of future lives in the community play an important role in evacuees’ decisions of whether to stay in the pre-Katrina communities. Race, risk, and damage done are also valid predictors of return decisions. This finding emphasizes the importance of both governmental initial response to the disaster and effective communication of a clear vision toward a fully recovered community.
Article
One of the most important tasks of urban and hazard planning is to mitigate the damages and minimize the costs of the recovery process after catastrophic events. In this context, the capability of urban systems and communities to recover from disasters is referred to as resilience. Despite the problem of resilience quantification having received a lot of attention, a mathematical definition of the resilience of an urban community, which takes into account the social aspects of an urban environment, has not yet been identified. In this article, we provide and test a methodology for the assessment of urban resilience to catastrophic events which aims at bridging the gap between the engineering and the ecosystem approaches to resilience. We propose to model an urban system by means of different hybrid social–physical complex networks, obtained by enriching the urban street network with additional information about the social and physical constituents of a city, namely citizens, residential buildings, and services. Then, we introduce a class of efficiency measures on these hybrid networks, inspired by the definition of global efficiency given in complex network theory, and we show that these measures can be effectively used to quantify the resilience of an urban system, by comparing their respective values before and after a catastrophic event and during the reconstruction process. As a case study, we consider simulated earthquakes in the city of Acerra, Italy, and we use these efficiency measures to compare the ability of different reconstruction strategies in restoring the original performance of the urban system.
Article
This paper proposes a new multi-stage framework to analyze infrastructure resilience. For each stage, a series of resilience-based improvement strategies are highlighted and appropriate correlates of resilience identified, to then be combined for establishing an expected annual resilience metric adequate for both single hazards and concurrent multiple hazard types. Taking the power transmission grid in Harris County, Texas, USA, as a case study, this paper compares an original power grid model with several hypothetical resilience-improved models to quantify their effectiveness at different stages of their response evolution to random hazards and hurricane hazards. Results show that the expected annual resilience is mainly compromised by random hazards due to their higher frequency of occurrence relative to hurricane hazards. In addition, under limited resources, recovery sequences play a crucial role in resilience improvement, while under sufficient availability of resources, deploying redundancy, hardening critical components and ensuring rapid recovery are all effective responses regardless of their ordering. The expected annual resilience of the power grid with all three stage improvements increases 0.034% compared to the original grid. Although the improvement is small in absolute magnitude due to the high reliability of real power grids, it can still save millions of dollars per year as assessed by energy experts. This framework can provide insights to design, maintain, and retrofit resilient infrastructure systems in practice.
Article
This article provides a comprehensive framework for conceptualizing, categorizing, and quantifying system performance measures in the presence of uncertain events, component failure, or other disruptions/disasters with the potential to reduce system capacity/performance. The framework clarifies the interrelationships between notions of coping capacity, preparedness, robustness, flexibility, recovery capacity, and resilience, previously espoused as independent measures, and provides a single mathematical decision problem for quantifying these measures congruously and maximizing their values. Required solution methodologies are presented for use in evaluating system performance in terms of these measures and resulting solutions can be exploited to determine an optimal allocation of limited resources to preparedness and response options. A numerical-transportation-related example is provided to illustrate its application. Results of this application offer insights into these various performance measures, their relationships, and the relative importance of preparedness and response actions.
Article
SUMMARY The present study evaluates seismic resilience of highway bridges that are important components of highway transportation systems. To mitigate losses incurred from bridge damage during seismic events, bridge retrofit strategies are selected such that the retrofit not only enhances bridge seismic performance but also improves resilience of the system consisting of these bridges. To obtain results specific to a bridge, a reinforced concrete bridge in the Los Angeles region is analyzed. This bridge was severely damaged during the Northridge earthquake because of shear failure of one bridge pier. Seismic vulnerability model of the bridge is developed through finite element analysis under a suite of time histories that represent regional seismic hazard. Obtained bridge vulnerability model is combined with appropriate loss and recovery models to calculate seismic resilience of the bridge. Impact of retrofit on seismic resilience is observed by applying suitable retrofit strategy to the bridge assuming its undamaged condition prior to the Northridge event. Difference in resilience observed before and after bridge retrofit signified the effectiveness of seismic retrofit. The applied retrofit technique is also found to be cost-effective through a cost-benefit analysis. First order second moment reliability analysis is performed, and a tornado diagram is developed to identify major uncertain input parameters to which seismic resilience is most sensitive. Statistical analysis of resilience obtained through random sampling of major uncertain input parameters revealed that the uncertain nature of seismic resilience can be characterized with a normal distribution, the standard deviation of which represents the uncertainty in seismic resilience. Copyright © 2013 John Wiley & Sons, Ltd.
Article
In this paper, we have reviewed various approaches to defining resilience and the assessment of resilience. We have seen that while resilience is a useful concept, its diversity in usage complicates its interpretation and measurement. In this paper, we have proposed a resilience analysis framework and a metric for measuring resilience. Our analysis framework consists of system identification, resilience objective setting, vulnerability analysis, and stakeholder engagement. The implementation of this framework is focused on the achievement of three resilience capacities: adaptive capacity, absorptive capacity, and recoverability. These three capacities also form the basis of our proposed resilience factor and uncertainty-weighted resilience metric. We have also identified two important unresolved discussions emerging in the literature: the idea of resilience as an epistemological versus inherent property of the system, and design for ecological versus engineered resilience in socio-technical systems. While we have not resolved this tension, we have shown that our framework and metric promote the development of methodologies for investigating “deep” uncertainties in resilience assessment while retaining the use of probability for expressing uncertainties about highly uncertain, unforeseeable, or unknowable hazards in design and management activities.
Article
Resilience is generally understood as the ability of an entity to recover from an external disruptive event. In the system domain, a formal definition and quantification of the concept of resilience has been elusive. This paper proposes generic metrics and formulae for quantifying system resilience. The discussions and graphical examples illustrate that the quantitative model is aligned with the fundamental concept of resilience. Based on the approach presented it is possible to analyze resilience as a time dependent function in the context of systems. The paper describes the metrics of network and system resilience, time for resilience and total cost of resilience. Also the paper describes the key parameters necessary to analyze system resilience such as the following: disruptive events, component restoration and overall resilience strategy. A road network example is used to demonstrate the applicability of the proposed resilience metrics and how these analyses form the basis for developing effective resilience design strategies. The metrics described are generic enough to be implemented in a variety of applications as long as appropriate figures-of-merit and the necessary system parameters, system decomposition and component parameters are defined.
Article
This paper deals with a novel technique that jointly uses structural fragility analysis, network flow analysis, and random field theory to assess the correlation among the damage levels of bridges in a transportation network under extreme events, and to estimate the sensitivity of the network performance to the correlation distance. A stochastic computational framework for the combined use of the individual bridge damage level due to extreme events and the bridge network performance evaluation is presented. Random field theory is used to simulate the bridge damage level, so that it is possible to directly control its correlation and perform a parametric analysis.Two numerical examples that involve bridges in parallel and series configurations subject to extreme events (e.g. earthquakes) show that the correlation distance of the damage can strongly affect the network performance indicators. Therefore, this correlation should be taken into account for every analysis that involves the network performance assessment.
Article
This paper demonstrates the concept of disaster resilience through the development and application of quantitative measures. As the idea of building disaster-resilient communities gains acceptance, new methods are needed that go beyond estimating monetary losses and that address the complex, multiple dimensions of resilience. These dimensions include technical, organizational, social, and economic facets. This paper first proposes resilience measures that relate expected losses in future disasters to a community's seismic performance objectives. It then demonstrates these measures in a case study of the Memphis, Tennessee, water delivery system. An existing earthquake loss estimation model provides a starting point for quantifying resilience. The analysis compares two seismic retrofit strategies and finds that only one improves community resilience over the status quo. However, it does not raise resilience to an adequate degree. The exercise demonstrates that the resilience framework can be valuable for guiding mitigation and preparedness efforts. However, to fully implement the concept, new research on resilience is needed that goes beyond loss estimation modeling.
Article
Resilience is the ability of the system to both absorb shock as well as to recover rapidly from a disruption so that it can return back to its original service delivery levels or close to it. The trans-oceanic telecommunication fiber-optics cable network that serves as the backbone of the internet is a particularly critical infrastructure system that is vulnerable to both natural and man-made disasters. In this paper, we propose a model to measure the base resiliency of this network, and explore the node to node and the overall resiliency of the network using existing data for demand, capacity and flow information. The submarine cable system is represented by a network model to which hypothetical disruptions can be introduced. The base resiliency of the system can be measured as the ratio of the value delivery of the system after a disruption to the value deliver of the system before a disruption. We further demonstrate how the resiliency of the trans-oceanic telecommunication cable infrastructure is enhanced through vulnerability reduction.
Article
This paper presents a multimodal trip distribution function estimated and validated for the metropolitan Washington region. In addition, a methodology for measuring accessibility, which is used as a measure of effectiveness for networks, using the impedance curves in the distribution model is described. This methodology is applied at the strategic planning level to alternative HOV alignments to select alignments for further study and Right-of-Way preservation.
Article
THIS REVIEW EXPLORES BOTH ECOLOGICAL THEORY AND THE BEHAVIOR OF NATURAL SYSTEMS TO SEE IF DIFFERENT PERSPECTIVES OF THEIR BEHAVIOR CAN YIELD DIFFERENT INSIGHTS THAT ARE USEFUL FOR BOTH THEORY AND PRACTICE. THE RESILIENCE AND STABILITY VIEWPOINTS OF THE BEHAVIOR OF ECOLOGICAL SYSTEMS CAN YIELD VERY DIFFERENT APPROACHES TO THE MANAGEMENT OF RESOURCES. THE STABILITY VIEW EMPHASIZES THE EQUILIBRIUM, THE MAINTENANCE OF A PREDICTABLE WORLD, AND THE HARVESTING OF NATURE'S EXCESS PRODUCTION WITH AS LITTLE FLUCTUATION AS POSSIBLE. THE RESILIENCE VIEW EMPHASIZES DOMAINS OF ATTRACTION AND THE NEED FOR PERSISTENCE. BUT EXTINCTION IS NOT PURELY A RANDOM EVENT: IT RESULTS FROM THE INTERACTION OF RANDOM EVENTS WITH THOSE DETERMINISTIC FORCES THAT DEFINE THE SHAPE, SIZE AND CHARACTERISTICS OF THE DOMAIN OF ATTRACTION. THE VERY APPROACH, THEREFORE, THAT ASSURES A STABLE MAXIMUM SUSTAINED YIELD OF A RENEWABLE RESOURCE, MIGHT SO CHANGE THESE CONDITIONS THAT THE RESILIENCE IS LOST OR IS REDUCED SO THAT A CHANCE AND RARE EVENT THAT PREVIOUSLY COULD BE ABSORBED CAN TRIGGER A SUDDEN DRAMATIC CHANGE AND LOSS OF STRUCTURAL INTEGRITY OF THE SYSTEM. A MANAGEMENT APPROACH BASED ON RESILIENCE, ON THE OTHER HAND, WOULD EMPHASIZE THE NEED TO KEEP OPTIONS OPEN, THE NEED TO VIEW EVENTS IN A REGIONAL RATHER THAN A LOCAL CONTEXT, AND THE NEED TO EMPHASIZE HETEROGENEITY. THE RESILIENCE FRAMEWORK DOES NOT REQUIRE A PRECISE CAPACITY TO PREDICT THE FUTURE BUT ONLY A QUALITATIVE CAPACITY TO DEVISE SYSTEMS THAT CAN ABSORB AND ACCOMMODATE FUTURE EVENTS IN WHATEVER UNEXPECTED FORM THEY MAY TAKE.
Article
This paper introduces an approach to assess and improve the time-dependent resilience of urban infrastructure systems, where resilience is defined as the systems' ability to resist various possible hazards, absorb the initial damage from hazards, and recover to normal operation one or multiple times during a time period T. For different values of T and its position relative to current time, there are three forms of resilience: previous resilience, current potential resilience, and future potential resilience. This paper mainly discusses the third form that takes into account the systems' future evolving processes. Taking the power transmission grid in Harris County, Texas, USA as an example, the time-dependent features of resilience and the effectiveness of some resilience-inspired strategies, including enhancement of situational awareness, management of consumer demand, and integration of distributed generators, are all simulated and discussed. Results show a nonlinear nature of resilience as a function of T, which may exhibit a transition from an increasing function to a decreasing function at either a threshold of post-blackout improvement rate, a threshold of load profile with consumer demand management, or a threshold number of integrated distributed generators. These results are further confirmed by studying a typical benchmark system such as the IEEE RTS-96. Such common trends indicate that some resilience strategies may enhance infrastructure system resilience in the short term, but if not managed well, they may compromise practical utility system resilience in the long run.
Article
(1) A procedure has been described for the qualitative analysis of insect outbreak systems using spruce budworm and balsam fir as an example. This consists of separating the state variables into fast and slow categories. (2) The dynamics of the fast variables are analysed first, holding the slow variables fixed. Then the dynamics of the slow variables are analysed, with the fast variables held at corresponding equilibrium values. If there are several such equilibria, there are several possibilities for the slow dynamics. (3) In the case of the budworm, this analysis exhibits the possibility of `relaxation oscillations' which are familiar from theory of the Van der Pol oscillator. In more modern terminology, the jumps of the system are governed by a cusp catastrophe. (4) Such an analysis can be made on the basis of qualitative information only, but additional insight emerges when parameter ranges are defined by the kind of information typically available from an experienced biologist. (5) At the least this can be a guide to assess subsequent priorities for both research and policy.
Book
Notations. Preface. Part I: Project Management: Basics and Scheduling Problems. 1. The Project Management Process. 2. Project Planning and Control. 3. Resource-Constrained Scheduling Problems. Part II: Resource-Constrained Project Scheduling: Solution Methods. 4. Lower Bound Methods. 5. Heuristic Procedures. 6. Exact Procedures. 7. Computational Expirements. 8. Summary and Conclusions. References. Index.
Article
The transport planning process as it is usually carried out consists of a number of stages. This paper considers commonly used models for two of these stages, trip distribution and traffic assignment, and derives models combining them into a single stage.The trip distribution stage of the transport planning is concerned with estimating the number of trips per unit time which will be made between each pair of zones in the study area. The models considered are all gravity models so that the estimated pattern of trips depends on the costs of travel between the various pairs of zones and these costs have usually been calculated from fixed costs associated with the links of the transport network. It is known, however, that the cost of travelling along a link increases with the amount of traffic using the link, and this is taken into account in the model used at the traffic assignment stage when the trip demands obtained from the trip distribution model are allocated to routes through the network. The link costs which correspond to the final estimated traffic flows obtained from the traffic assignment model are, however, not in general the same as those assumed at the trip distribution stage. In this paper this problem is overcome by combining trip distribution and traffic assignment into one stage and describing them by one model. The combined model is then reformulated as an equivalent optimatization problem which is solved.
Article
This paper conducts an analysis to assess the significance of highway network links in Maryland under flood damage. An accessibility index is derived to incorporate the distance-decay effect and the volume of traffic influence on the transportation network. The accessibility level of individual counties and the state as a whole is checked before and after the hypothetical disruption of individual links within the floodplain. The results indicate that critical links identified based on the distance-only and the distance-traffic volume criteria appear to be different, implying that the priority of retrofit might also vary depending on what criterion to choose. The percentage loss of accessibility due to the disruption of a link is generally greater in the latter. However, distance-only consideration results in a more prominent spatial distribution pattern of links in percentage loss induced. Some links remain significant in both cases. Especially if the disruption of a certain link does not have an alternative solution (for example, if the link is the only way in and out of a certain county) and if counties connected by the link are low accessibility counties, the two criteria may produce a similar outcome.
Article
The resource-constrained project scheduling problem (RCPSP) consists of activities that must be scheduled subject to precedence and resource constraints such that the makespan is minimized. It has become a well-known standard problem in the context of project scheduling which has attracted numerous researchers who developed both exact and heuristic scheduling procedures. However, it is a rather basic model with assumptions that are too restrictive for many practical applications. Consequently, various extensions of the basic RCPSP have been developed. This paper gives an overview over these extensions. The extensions are classified according to the structure of the RCPSP. We summarize generalizations of the activity concept, of the precedence relations and of the resource constraints. Alternative objectives and approaches for scheduling multiple projects are discussed as well. In addition to popular variants and extensions such as multiple modes, minimal and maximal time lags, and net present value-based objectives, the paper also provides a survey of many less known concepts.
Article
There have been many survey papers in the area of project scheduling in recent years. These papers have primarily emphasized modeling and algorithmic contributions for specific classes of project scheduling problems, such as net present value (NPV) maximization and makespan minimization, with and without resource constraints. Paralleling these developments has been the research in the area of project scheduling decision support, with its emphasis on data sets, data generation methods, and so on, that are essential to benchmark, evaluate, and compare the new models, algorithms and heuristic techniques. These investigations have extended the frontiers of research and application in all areas of project scheduling and management. In this paper, we survey the vast literature in this area with a perspective that integrates models, data, and optimal and heuristic algorithms, for the major classes of project scheduling problems. We also include recent surveys that have compared commercial project scheduling systems. Finally, we present an overview of web-based decision support systems and discuss the potential of this technology in enabling and facilitating researchers and practitioners in identifying new areas of inquiry and application.
Article
Two of the primary measures that characterize the concept of disaster resilience are the initial impact of a disaster event and the subsequent time to recovery. This paper presents a new analytic approach to representing the relationship between these two characteristics by extending a multi-dimensional approach for predicting resilience into a technique for fitting the resilience function to the preferences and priorities of a given decision maker. This allows for a more accurate representation of the perceived value of different resilience scenarios to that individual, and thus makes the concept more relevant in the context of strategic decision making.