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Multiple attribute decision making: an introduction
... Experienced mechanical engineers have affirmed this parameter. The technique for order preference by similarity to ideal solution (TOPSIS) is a widely used method of multi-objective decision making to optimize parameters, which was proposed by Hwang and Yoon (1981) [45]. It encompasses both the ideal alternatives and the negative ideal alternatives and is convenient to calculate [46]. ...
... Experienced mechanical engineers have affirmed this parameter. The technique for order preference by similarity to ideal solution (TOPSIS) is a widely used method of multi-objective decision making to optimize parameters, which was proposed by Hwang and Yoon (1981) [45]. It encompasses both the ideal alternatives and the negative ideal alternatives and is convenient to calculate [46]. ...
... Experienced mechanical engineer affirmed this parameter. The technique for order preference by similarity to ideal so (TOPSIS) is a widely used method of multi-objective decision making to optimize p eters, which was proposed by Hwang and Yoon (1981) [45]. It encompasses both th alternatives and the negative ideal alternatives and is convenient to calculate [46 entropy method is used to calculate the weight of each evaluation index [47]. ...
Rubber seals have been widely applied in mechanical sealing structures in various fields such as automobiles, aerospace, and deep-sea hydraulic systems. The current analysis methods for O-ring sealing performance mainly include experiments and simulations. This study takes the motor sealing structure as the research object and proposes a multi-objective optimization method for designing sealing structures. Based on the finite element analysis model, the main indicators related to sealing performance were obtained. These indicators transfer to multi-objective optimization analysis to determine the influence of different groove depths on sealing performance. The analysis results show that when the bolt preload is 50 N, a groove depth of 0.9 mm is the optimal design scheme. The optimal relationship between the O-ring diameter D and the sealing structure groove depth is H = 0.6 D. Moreover, a prototype test under the condition of IPX7 requirement verifies the optimal design scheme’s waterproof performance. The proposed method provides multiple design schemes for comprehensive evaluation considering different sealing structures. It reveals that the sealing performance is not only determined by rubber material characteristics but also by seal structure dimension.
... Our system introduces three key innovations: (1) an adaptive -selection mechanism leveraging TOPSIS-based multi-criteria decision analysis (MCDA) [4] to align privacy settings with public priorities; (2) explainable noise injection with real-time Mean Absolute Error (MAE) visualizations and GPT-4-powered impact analysis to enhance transparency and trust; and (3) dynamic legal-compliance constraints that adjust privacy budgets to evolving regulations. ...
... • Preference Elicitation: Users specify priorities via sliders for privacy (1)(2)(3)(4)(5), accuracy (1-5), legal compliance (yes/no), and data sensitivity (1-3). ...
... Adaptive Selection: Implements TOPSIS multi-criteria decision analysis[4] to resolve trade-offs: ...
This paper introduces a conversational interface system that enables participatory design of differentially private AI systems in public sector applications. Addressing the challenge of balancing mathematical privacy guarantees with democratic accountability, we propose three key contributions: (1) an adaptive -selection protocol leveraging TOPSIS multi-criteria decision analysis to align citizen preferences with differential privacy (DP) parameters, (2) an explainable noise-injection framework featuring real-time Mean Absolute Error (MAE) visualizations and GPT-4-powered impact analysis, and (3) an integrated legal-compliance mechanism that dynamically modulates privacy budgets based on evolving regulatory constraints. Our results advance participatory AI practices by demonstrating how conversational interfaces can enhance public engagement in algorithmic privacy mechanisms, ensuring that privacy-preserving AI in public sector governance remains both mathematically robust and democratically accountable.
... In 1981, Hwang and Yoon developed the TOPSIS model to address MCDM problem [35,36]. The core concept of this technique is that the chosen decision alternative should be as close as possible to the PIS, which represents the best level for all attributes, and as far away as possible from the NIS, which represents the worst level for all attributes [36][37][38][39][40][41]. ...
... In 1981, Hwang and Yoon developed the TOPSIS model to address MCDM problem [35,36]. The core concept of this technique is that the chosen decision alternative should be as close as possible to the PIS, which represents the best level for all attributes, and as far away as possible from the NIS, which represents the worst level for all attributes [36][37][38][39][40][41]. This approach assumes that each criterion has a tendency to either monotonically increase or decrease in utility, making it easier to identify the PIS and NIS. ...
... In this study, the TOPSIS model is proposed to rank the most preferred courier services. TOPSIS data analysis is performed in seven steps [36]. ...
Courier services are businesses that deliver documents, parcels and heavy products from one place to another. Courier services are gaining popularity nowadays due to their efficient and reliable delivery. However, the existence of many courier service companies today has led to fierce commercial competition both domestically and globally. Since there are many decision alternatives and criteria to consider, consumers face a significant challenge in choosing the best courier service. As a result, selecting the optimal courier service involves a process of Multi-Criteria Decision Making (MCDM). The objective of this study is to determine the preferred courier service based on undergraduates’ preferences using an integrated AHP-TOPSIS model. The AHP-TOPSIS model is proposed in this study to tackle the MCDM problem as choosing the optimal courier service involves various decision criteria. In this research, AHP is proposed to identify the priority of decision criteria, whereas TOPSIS is utilized to determine the ranking of the courier service providers. Additionally, this study aims to determine the priority of decision criteria. As a result of this research, GD Express was identified as the most preferred courier service provider, followed by DHL, FedEx, Skynet Express, PosLaju, and City-Link Express. Furthermore, the top three influencing factors are freight rates, timeliness and reliability. The significance of this study lies in identifying the most preferred courier service and the most influential decision criterion in the decision-making process. The study can serve as a reference for the less popular courier service companies, assisting them in identifying weaknesses and making enhancements according to the decision criteria’ ranking.
... Consequently, any criterion where COV exhibits greater values than others is more significant, as its relative weight within the COV is higher, resulting in the enhanced discriminating power of the criterion in differentiating the alternatives. Entropy method [44,46]. The entropy method measures the information content in each criterion using Shannon's entropy concept, where the key idea is to assign weights based on the amount of information present in the criteria. ...
... Simple additive weighting (SAW) [46,50]. The SAW method is one of the oldest techniques in the MCDM field, and its popularity is owing to its relative simplicity and ease of computation. ...
... TOPSIS [46,51]. The TOPSIS method is a widely utilized MCDM method that ranks alternatives based on relative closeness to a positive ideal solution (PIS) and a negative ideal solution (NIS). ...
This paper presents a cradle-to-gate sustainability assessment methodology specifically designed to evaluate aircraft components in a robust and systematic manner. This methodology integrates multi-criteria decision-making (MCDM) analysis across ten criteria, categorized under environmental impact, cost, and performance. Environmental impact is analyzed through lifecycle assessment and cost through lifecycle costing, with both analyses facilitated by SimaPro 9.6.0.1 software. Performance is measured in terms of component mass and specific stiffness. The robustness of this methodology is tested through various MCDM techniques, normalization approaches, and objective weighting methods. To demonstrate the methodology, this paper assesses the sustainability of a fuselage panel, comparing nine variants that differ in materials, joining techniques, and part thicknesses. All approaches consistently identify thermoplastic CFRP panels as the most sustainable option, with the geometric mean aggregation of weights providing balanced criteria consideration across environmental, cost, and performance aspects. The adaptability of this proposed methodology is illustrated, showing its applicability to any aircraft component with the requisite data. This structured approach offers critical insights to support sustainable decision-making in aircraft component design and procurement.
... The 'technique for order of preference by similarity to ideal solution' (TOPSIS) is a widely adopted MCDM ranking method for analysing financial performance due to its quantitative attributes and simple computational procedure (Hsu, 2013). Its main principle is that the best alternatives are those with the shortest distance from the positive ideal solutions (PISs) and the greatest distance from the negative ideal solutions (NISs) (Athawale and Chakraborty, 2011;Yoon and Hwang, 1995). PIS is the maximum value for a benefit criterion and NIS is the minimum value, whereas the opposite is true for the cost criterion (Ksenija et al., 2017;Obaid et al., 2022). ...
... TOPSIS is an MCDM method in which the rankings of the alternatives are based on their proximity to the PISs and the distance from the NISs. This study employs the TOPSIS method proposed by Yoon and Hwang (1995) as follows: ...
... TOPSIS, introduced by Hwang and Yoon [27], is a method for ranking alternatives based on their proximity to the ideal solution. The core principle of the TOPSIS evaluation method involves identifying the positive and negative ideal solutions among the finite options based on the normalized decision matrix. ...
... Step 3: Establishing the Lagrange equation to solve Equation (27). ...
In response to the threat assessment challenge posed by unmanned aerial vehicles (UAVs) in air defense operations, this paper proposes a dynamic assessment model grounded in fuzzy multi-attribute decision making. First, a three-dimensional evaluation index system is established, encompassing capability, opportunity, and intention. Quantification functions for assessing the threat level of each attribute are then designed. To account for the temporal dynamics of the battlefield, an innovative fusion approach is developed, integrating inverse Poisson distribution time weights with subjective–objective comprehensive weighting, thereby establishing a dynamic variable weight fusion mechanism. Among these, the subjective weights are determined by integrating the intention probability matrix, effectively incorporating the intentions into the threat assessment process to reflect their dynamic changes and enhancing the overall evaluation accuracy. Leveraging the improved technique for order preference by similarity to ideal solution (TOPSIS), the model achieves threat prioritization. Experimental results demonstrate that this method significantly enhances the reliability of threat assessments in uncertain and dynamic battlefield environments, offering valuable support for air defense command and control systems.
... The TOPSIS method is the second most important and practical MCDM method from the hierarchical analysis process. It was developed by Hwang andYoon in 1981 (Hwang, Yoon, 1981). This method is simple and easy to use and applies to problems with a large (Çelikbilek, Tüysüz, 2020). ...
... The TOPSIS method is the second most important and practical MCDM method from the hierarchical analysis process. It was developed by Hwang andYoon in 1981 (Hwang, Yoon, 1981). This method is simple and easy to use and applies to problems with a large (Çelikbilek, Tüysüz, 2020). ...
In recent years, the shortage of forest resources and the increase in demand for wooden products have faced severe challenges in the wood and paper industry. According to the surveys conducted, the branches and waste from palm pruning can be used for conversion industries, including the production of chipboard and medium-density fiberboard (MDF). The surface of Iran has significant coverage of palm trees, and currently, a large amount of waste from these trees is thrown away and burned. Therefore, the topic chosen in this research is to determine the location for building the wooden products production factory, aiming at optimal use of palm waste and helping to compensate for the lack of wooden production in the country. First of all, suitable criteria for building a wooden products factory are determined through sources and experts" opinions. Then, they are prioritised and weighted using a questionnaire based on the BWM method. In the next step, ArcGIS software is used to apply the criteria on the level under investigation. Decision options are ranked using TOPSIS, ARAS, COPRAS, WASPAS, MULTIMOORA, VIKOR, SAW and CODAS decision-making methods. Then the obtained results are collected using the CRITIC method, and the best construction places are determined. When different decision-making methods are combined, the accuracy and strength of the obtained results also increase.
... The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is one of the most frequently used Multiple Criteria Decision Making (MCDM) techniques and was originally introduced by (Hwang and Yoon 1981) and was further developed by S. J. Chen and Hwang (1992) and Yoon and Hwang (1995) to manage complex decision-making problems. The method has been applied in a variety of fields like engineering and environmental studies (Motia and Reddy, 2020;Afzali Behbahani, Khodadadi Karimvand, and Ahmadi 2022;Asadabadi et al. 2023;Gorgij, Wu, and Moghadam 2019;Hasanzadeh et al. 2023;Rani and Kaushal 2022;Z. ...
Lighting is a key factor supporting the visual and nonvisual needs of humans.LED lighting systems dominate all contemporary lighting installations allover the world. However, the evolution of knowledge of lighting sciencehas set in attention various counterbalancing factors for proper lightingdesign such as lighting levels, glare, and melanopic illuminance.Multicriteria decision making methodologies are valuable tools that arecharacterized by numerous advantages aiding decision makers in selectingthe optimal alternative. This paper introduces a multicriteria decision supportmethod utilizing visual, circadian, energy, and cost criteria fora comprehensive assessment of modern LED lighting systems. Six criteriaare proposed so as to assess holistically the technical and economic attri-butes of LED lighting systems and ensure their applicability to office lighting.Laboratory photometric, energy, and spectral measurements and lightingsimulations upon 10 types of LED luminaires are performed so as to quantifytheir performance on each criterion. Finally, the Technique for Order ofPreference by Similarity to Ideal Solution (TOPSIS) multicriteria method isapplied, which ranks the 10 types of LED lighting systems and determines theoptimal selection
... The AHP method simplifies complex decisions by breaking them down into a hierarchy of straightforward forms that can be evaluated subjectively. It assists the decision-makers in determining the relative influence of different elements through pairwise comparison [167]. Wankhade et al. [168] classified the landslide-prone slopes in sections of Pithoagarh, Chamoli, Rudraprayag, Bageshwar, Tehri Garhwal, Pauri Garhwal, Nainital & Uttarkashi districts using the weighted multiclass index overlay method. ...
Landslides are the most common of all natural hazards. Climatic changes, increasing population, unplanned urbanisation and increasing connectivity to the hilly regions are the prime contributors to landslides. Chamoli, the second largest district of Uttarakhand state, is home to many pilgrims and tourist spots that are visited by millions every year. It is also a zone surrounded by several thrusts/faults that in association with human interference initiate the risk of landslides and land subsidence in the region. The district holds limited studies related to landslide susceptibility and risk assessment compared to the other districts of the state. Thus, the current review article focuses on comprehensively analysing various remote sensing and geotechnical investigation-based methods deployed for the monitoring, evaluation and prediction of landslide susceptibility and risk in the region of Chamoli. Lack of connectivity, unscientific planning and improper implementation of technologies in past were the factors for not having a proper landslide risk assessment in the zone. Among the various remote sensing and geotechnical investigation-based methods that are being used globally for landslide susceptibility and risk assessment, only a few have been used in the Chamoli region of which the multi-class index overlay techniques and hybrid machine learning methods were the most widely used in the region. Thus, the study area requires more scientific exploration and studies to have a better assessment of landslide susceptibility and risk which couldn’t be possible due to poor connectivity and unavailability of proper data in the past.
... Applied in several areas, such as logistics, TOPSIS evaluates strategies considering criteria such as cost, time, accessibility and environmental impact, guiding decisions in indigenous communities (Yoon & Hwang, 1995;Freitas et al., 2022). Normalize the decision matrix to make the criteria comparable, especially when they have different units. ...
Objective: To present an applied study to identify and propose logistics indicators that help reduce the vulnerabilities of indigenous communities in the South and Southeast of Pará, supporting more effective public policies adapted to the local reality. Theoretical Framework: Addresses the logistical difficulties of these communities, such as geographic barriers, precarious infrastructure and limited access to essential services. Method: Research based on bibliographic review, document analysis and case study, focusing on mapping vulnerabilities and developing relevant indicators for logistics management using methods such as VFT, TOPSSIS. Results and Discussion: A conceptual model was developed with indicators such as proximity to health units and transportation routes, which allow monitoring and improving access to essential resources. Research Implications: The indicators created are useful tools for planning and implementing logistics public policies that reduce vulnerabilities and improve access to services in indigenous communities. Originality/Value: The study presents a proposal adapted to the specificities of the South and Southeast of Pará, contributing with an innovative model for future research and actions in similar regions.
... Developed initially in 1981 by Ching-Lai Hwang and Yoon [70] and subsequently refined [71,72], Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) operates on a compensatory principle. The method ranks alternatives by evaluating their geometric distances from two hypothetical benchmarks: a positive ideal solution and a negative ideal solution. ...
... Therefore, the redundant coding strategy mentioned in [14] and [18] is adopted in this paper, in which the number of reference values of antecedent attributes and the number of consequence ranks are present, and parameters in the rule base are coding in redundant. According to psychologists, 7±2 is the limit of human ability in information processing [29]. Therefore, the maximum number of the reference values of attributes and the maximum number of consequence ranks are both set to 9, and all individuals are coded according to the maximum number of genes. ...
The belief rule-based (BRB) system has been popular in complexity system modeling due to its good interpretability. However, the current mainstream optimization methods of the BRB systems only focus on modeling accuracy but ignore the interpretability. The single-objective optimization strategy has been applied in the interpretability-accuracy trade-off by integrating accuracy and interpretability into an optimization objective. But the integration has a greater impact on optimization results with strong subjectivity. Thus, a multi-objective optimization framework in the modeling of BRB systems with interpretability-accuracy trade-off is proposed in this paper. Firstly, complexity and accuracy are taken as two independent optimization goals, and uniformity as a constraint to give the mathematical description. Secondly, a classical multi-objective optimization algorithm, nondominated sorting genetic algorithm II (NSGA-II), is utilized as an optimization tool to give a set of BRB systems with different accuracy and complexity. Finally, a pipeline leakage detection case is studied to verify the feasibility and effectiveness of the developed multi-objective optimization. The comparison illustrates that the proposed multi-objective optimization framework can effectively avoid the subjectivity of single-objective optimization, and has capability of joint optimizing the structure and parameters of BRB systems with interpretability-accuracy trade-off.
... Metode Weighted Product (WP) merupakan metode untuk menyelesaikan Multi Attribute Decision Making (MADM). Weighted Product (WP) menggunakan teknik perkalian untuk menghubungkan rating attribute, di mana peringkat tiap atribut harus dipangkatkan terlebih dahulu dengan atribut bobot yang bersangkutan [21]. Langkah-langkah penyelesaian masalah menggunakan metode Weighted Product (WP) untuk pemilihan alternatif mustahiq zakat adalah sebagai berikut: 1) Penentuan kriteria yang dijadikan dasar dalam penentuan mustahiq zakat Kriteria disimbolkan dengan Ci, di mana i merupakan banyaknya kriteria yang ditentukan untuk dijadikan acuan dalam pengambilan keputusan. ...
Zakat is part of a person's assets, which according to Islam, if the assets exceed the nishab limit, the owner is obliged to hand them over to someone who has the right to receive them under certain conditions or is called mustahiq zakat. To determine zakat mustahiq, BAZNAS Solok City collects data on prospective zakat recipients and determines mustahiq based on criteria determined manually. Therefore, through this research, the Simple Additive Weighting (SAW) and Weighted Product (WP) methods are used to determine mustahiq zakat so that it can help BAZNAS Solok City in making decisions. There are five criteria used, residence status, monthly income, employment status, number of dependents, and monthly expenses. Monthly income is a cost criterion and the other is a profit criterion. After carrying out calculations using both methods, ranking results were obtained from prospective zakat recipients (mustahiq). In the SAW Method, the first ranking results were obtained for the fourth (A4) and ninth (A9) recipient candidates, as well as in the WP Method. However, there is a difference in ranking between third and fourth. It can be seen that the SAW and WP methods provide almost the same ranking results, but there are differences in several ranking orders even though the best rankings are in the same alternative. Through the sensitivity test, the results were obtained that the WP method has a higher sensitivity than the SAW method, that is 4,14% > 3,17%, so it can be concluded that the WP method is better used as decision support by decision makers, is BAZNAS Solok City.
... The TOPSIS model, originally proposed by Ching-Lai Hwang and Yoon in 1981 [34], was subsequently refined by Yoon [35], Hwang, and later by Lai and Liu [36]. The implementation of the TOPSIS methodology involves the following steps. ...
The transition toward sustainable construction practices has intensified the demand for intelligent and energy-efficient building components, particularly smart window technologies. While numerous innovations exist, the selection of the most optimal smart window solution is difficult due to the trade-offs among conflicting criteria such as energy performance, economic feasibility, environmental impact, and user comfort. This study proposes an integrated Fuzzy Multi-Criteria Decision-Making (FMCDM) framework for selecting smart window technologies. The methodology combines the Fuzzy Analytic Hierarchy Process (FAHP) to determine criterion weights and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank alternatives. Nine sustainability-related criteria across the environmental, economic, and social dimensions were evaluated using expert input. The results identify thermochromic smart windows as the optimal choice. This research contributes a structured, adaptable, and scalable FMCDM framework for sustainable technology selection, with broader applicability to green product design and decision-making in the construction and energy sectors.
... The MSE-TOPSIS model is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution and the longest geometric distance from the negative ideal solution (Yoon and Hwang, 1995). The MSE-TOPSIS model uses a simple computation process. ...
China has suffered a significant urban sprawl in a rapidly urbanizing process. The trial urban growth boundary (UGB) delineation can help control urban sprawl, and these changes in urban growth have deep effects on land carrying capacity (LCC). This study characterizes the effects of trial UGB delineation on LCC in China. LCC which was subdivided into three components: economic carrying capacity, social carrying capacity, and ecological carrying capacity of land was assessed. Then the difference-in-difference model was further employed to quantify the associations between trial UGB delineation and LCC. The results showed trial UGB delineation has a significant negative impact on the economic carrying capacity of land (coefficients of DID are −0.057 and −0.059). Trial UGB delineation has significant positive impacts on the social carrying capacity (coefficients of DID are 0.051 and 0.031) and ecological carrying capacity of land (coefficients of DID are 0.030 and 0.027). Meanwhile, the effects of trial UGB delineation on the three components of LCC are heterogeneous in the eastern, central, and western regions. Besides, the heterogeneous effects of UGB delineation on the three components of LCC have existed adding dummy variables of urban hierarchy. Based on the findings, targeted policy recommendations include adopting regionally differentiated UGB adjustment mechanisms, integrating dynamic resource-carrying capacity evaluation into UGB delineation, and establishing full-cycle UGB management.
... Although the selected indicators provide information on how different endpoints of the system can be vulnerable to droughts and heat, each indicator is measured using different parameters or classification schemes. This exerts the need to normalize the indicator scores if comparison and aggregation of indicators over a similar scale is required (Yoon and Hwang, 1995). Normalization schemes can be linear such as min-max or z-score approaches, non-linear such as benchmarking or using thresholds, and distance-based for example from a target value (Pollesch and Dale, 2016). ...
More frequent and intense drought and heat events imply increased multi-risks for urban green infrastructure (UGI) and their ecosystem services. To tackle this challenge, a conceptual drought and heat risk assessment framework has been developed. This study operationalizes the framework by providing a methodology that supports decision makers in their assessment, and selection of risk reduction alternatives. The methodology overlays two main procedures of the assessment: risk analysis and risk evaluation. Within the risk analysis, the risk system is delineated, from the drought and heat hazards, to the vulnerabilities of UGI entities, ecosystem functions (EF), and ecosystem services (ES). Urban parks, creeks, and lakes are used as exemplary UGI to derive biophysical system variables as so-called endpoints. A multi-layer approach is applied to translate the endpoints into an information system comprising descriptor, attribute, and indicator layers. The assignment of attributes and indicators to descriptors is based on a literature search. Hazard attributes are then linked with vulnerability indicators to derive risk indicators. A lane-based approach is adopted to interrelate indicators, and to identify the key indicators of the cascading nature of the system. The indicators "Net leaf-air temperature" and "Leaf net CO 2 assimilation" are determined as key indicators with 10 linkages each. As for the risk evaluation, a guideline is set to support the selection of methods for the multi-criteria evaluation. Based upon, methods such as the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are deemed especially applicable. Finally, the role of decision makers as end-users of the methodology and its local adoption is described together with principles for selecting these decision makers. A tool is designed to offer a simple and adaptive way to organize the calculation steps of the risk assessment, making it transferable and effective to use for researchers and practitioners of environmental risk management. Overall, the proposed methodology supports decision-making on drought and heat risks of UGI through systematic risk analysis and risk evaluation.
... Decision making merupakan proses pemilihan solusi dari alternatif-alternatif yang tersedia (Williams and Micallef 2009). Sedangkan, MADM merupakan alat bantu manajemen (pembuatan) keputusan yang diambil bertujuan untuk menilai perbandingan antara berbagai alternatif dengan mengacu pada beberapa kriteria sekaligus (Yoon and Hwang 1995). Penilaian performa bank syariah diimplementasikan melalui beberapa aspek dengan menerapkan pendekatan MADM. ...
Purpose – This study aims to explore and assess the performance of one of the Islamic rural banks in Indonesia based on the measurement of the maqashid sharia index (MSI). Method – This study relies on a quantitative descriptive approach by utilizing secondary data from the financial statements of Islamic rural banks Gebu Prima released by the FSA for 2021-2024. The method chosen to analyze this study's data is the simple additive weighting method with a multiple-attribute decision-making approach. This study uses three concepts: educating individuals, upholding justice, and promoting welfare. The MSI elements used in this study are educational grants, research, training, publicity, fair returns, functional distribution, interest-free products, profit ratio, personal income, and investment ratio in the real sector. Findings – This study's results indicate that the performance of the Islamic rural bank Gebu Prima has not been maximized because several MSI indicators have not been implemented. Implications – This research can provide insight and be a reference for future scientific studies. This research can encourage regulators to make more assertive policies related to determining performance measurement methods based on maqashid sharia so that the Islamic banking industry, such as Islamic rural banks, can improve its performance per the established guidelines.
... The methodology could be updated by integrating various multiple criteria decision analysis methods, including VIKROR (Opricovic & Tzeng, 2007), Compromise Programming (Zeleny, 1982), TOPSIS (Yoon & Hwang, 1995) etc. Additionally, Fuzzy Sets Theory (Zadeh, 1965) coupled with machine learning techniques can be useful in determining the spatial location of several evaluation criteria. ...
Despite the global pervasiveness of plastic pollution, research on identifying plastic contaminant zones remains limited, despite recent findings indicating widespread contamination across air, water, and soil. This study introduced an innovative methodology for identifying plastic contaminant zones by integrating Fuzzy Analytic Hierarchy Process with a decision support algorithm. Thirteen crucial geo-environmental and anthropogenic factors, including Runoff, Land Use/Land Cover, Air Quality Index, Normalized Difference Built-up Index (NDBI), Population Density, Tourist Sites, Dumping Grounds, Hospital Sites, Industrial Sites, Market Locations, Wastewater Treatment Plants, Road, and Canal Networks, are weighted using the proposed technique. The resulting map delineated plastic contaminant zones into categories of very high (12.93%), high (19.08%), moderate (25%), low (28.20%), and very low (14.80%) concentrations. Validation against socio-environmental indicators, focusing on Kolkata Metropolitan Development Authority’s contribution to SDG 3 (Good Health and Well-being), underscores the model’s effectiveness. Among the 4 Municipal Corporation, 37 Municipalities and 23 Panchayat Samities, Kolkata Municipal Corporation stands out with 51.69% of very high plastic contaminant zones, characterized by the lowest Total fertility rate (1.2 in 2011) and the highest dengue cases (4425 in 2023) as major implications of it. A soil sample was collected from a dumping site to check for the presence of plastic particles, revealing 70 plastic items within 500 g of soil. This systematic research approach not only provides actionable insights for municipal governments but also offers valuable guidance for regional and global researchers and policymakers.
... In this appendix, different steps of the TOPSIS MCDA method to develop sustainability indices for the sustainability criteria were described (adapted from Yoon and Hwang, [ 131 ]). A similar procedure is used to develop the overall environmental sustainability index. ...
Given the rapid growth of sustainable construction strategies globally and the importance of resiliency in civil infrastructure, it is crucial to adopt best practices. Modular construction is one such practice and is considered a better alternative to conventional construction in terms of resilience, construction times, resource efficiency, and sustainability. However, the continued expansion of modular construction relies on quantifying and evaluating its sustainability and the purported benefits. This paper develops and checks feasibility through an integrated multi-level decision support framework to empirically evaluate the sustainability performances of single-family residential modular homes. Criteria and indicator development and calculation, benchmark scale establishment, quantitative and qualitative data collection from literature and surveys, and multi-criteria decision analysis are unique aspects of this framework. The results of the two case studies located in the Okanagan region, Canada showed that modular homes perform at a higher level of sustainability than their conventional counterparts across multiple metrics and levels related to environmental and economic factors. The modular homes scored eco-efficiency values of 62.5 and 56.0, respectively and fell into higher performance range. The proposed framework offers flexibility in examining different dimensions of sustainability, providing valuable insights into the key parameters that need to be addressed to enhance overall sustainability. This research, which integrates life cycle thinking and decision-making, helps the construction industry and, municipalities, governments, and policymakers in making informed decisions on the selection of suitable construction methods in city developments and move towards a more resilient and sustainable sector.
... Behzadian et al. [4] summarized how PROMETHEE has been widely used and how it is robust across many fields. Yoon and Hwang [5] and Opricovic [7] have analyzed capabilities of TOPSIS and VIKOR, ...
This research aims at deep understanding of
similarity and dissimilarity of TOPSIS, VIKOR and
PROMETHEE methods respectively, which are very
popular in multi - criteria decision - making. We use
these methods in a real-life example and observe
their ranking results for the alternatives using the
vague values. The analysis shows that there are
differences in the accuracy, robustness and
sensitivity of the methods and this helps decision -
makers to choose the best method suited for their
purpose. This study illustrates the usefulness and
limitations of each method, emphasizing their pros
and cons. Also provides valuable insights for
researchers and decision - makers.
... Technique for order preference by similarity to ideal solution (TOPSIS) is a method for multiple-criteria decision-making. It operates based on relative distances between alternatives and imposes no strict constraints on sample size [23]. TOPSIS requires only minimal computation, possesses clear geometric significance, and has found widespread application across various fields. ...
Bridge condition assessment is a crucial component of bridge management. To better adapt to the multi-level, nonlinear, and multi-criteria decision-making problems in bridge assessments, a modified technique for order preference by similarity to ideal solution (TOPSIS)-based nonlinear method is proposed in a fuzzy environment. First, quantitative representations of three different types of bottom indices of bridge assessment models under the analytic hierarchy process framework are developed using fuzzy numbers. Subsequently, with regard to the conventional TOPSIS approach, several enhancement and optimizations are considered, including the absolutization and fuzzification of positive and negative ideal solutions, the determination of variable weights of bottom-level indexes, fuzzy assessment based on level sets, and the defuzzification and grading of the evaluation results. These measures reduce the ambiguities and uncertainties associated with the conventional TOPSIS approach and can optimally accommodate bridge performance evaluation in fuzzy logic. Finally, to illustrate the practicality and feasibility of the developing method, a real bridge assessment scenario is built. The results indicate that this approach can effectively reflect the real state of the overall bridge, providing a robust basis for bridge maintenance and rehabilitation decision-making.
... Next, the distances between each evaluation object and the optimal and worst solutions are calculated to determine the relative closeness of each evaluation alternative to the optimal solution. Finally, the alternatives are ranked based on this closeness, which serves as the basis for evaluating their superiority and inferiority [42].Rank Sum Ratio (RSR) Method: Zhao et al. proposed that the Rank Sum Ratio (RSR) method, developed by Tian Fengdiao in 1988, is a comprehensive evaluation technique that ranks evaluation indicators and converts them into a dimensionless statistical value, the RSR. This method uses parametric statistical analysis to determine the distribution of the RSR values and interpret the results. ...
To reduce and prevent traffic accidents, it is essential to transition from a reactive approach of "punishing after the fact to proactive preventive measures. This paper presents a traffic safety risk evaluation system for expressways, integrating 16 factors such as steering performance and road conditions. A model for assessing traffic safety risk on expressways is proposed using a combination of the AHP-TOPSIS-RSR approach. The AHP method helps form the evaluation matrix, while the TOPSIS method, incorporating entropy, is used to determine the relative closeness between the overall traffic safety risk index and ideal values. These values are then categorized based on expressway risk grades using a hierarchical standard. Additionally, a sensitivity analysis model is introduced through an orthogonal test to compute the sensitivity values of each factor and rank the most influential factors. The proposed method is validated through the Yongwu Expressway. The findings show that the safety risk of the Yongwu Expressway is rated as Level I, indicating a high-risk situation. The sensitivity values for factors like fatigue/unlicensed driving, vehicle speed, road layout, traffic flow, adverse weather conditions, and emergency response systems are 0.4721, 0.5088, 0.7598, 0.8142, 0.5296, and 0.4685, respectively, marking them as the most sensitive risk factors. The risk assessment accurately mirrors the traffic safety conditions of the Yongwu Expressway.
... A decision-making problem that considers many criteria seeks to choose the most suitable alternative from a set of options, as opposed to a strategy that only takes one criterion into account. AROMAN [34], when compared to other techniques such as MABAC [37], TOPSIS [38], ARAS [39], MAUT [40], CODAS [41], WASPAS [42], CoCoSo [43], VIKOR [44], and SWARA [45], exhibits notable differences. Most of these methods adhere to the same decision-making principles, the most important of which is the use of an initial decision-making matrix that incorporates a range of alternative options, assessed against a variety of often competing criteria. ...
With the increasing complexity of hotel selection, traditional decision-making models often struggle to account for uncertainty and interrelated criteria. Multi-criteria decision-making (MCDM) techniques, particularly those based on fuzzy logic, provide a robust framework for handling such challenges. This paper presents a novel approach to MCDM within the framework of Circular Intuitionistic Fuzzy Sets (C-IFS) by combining three distinct methodologies: Weighted Aggregated Sum Product Assessment (WASPAS), an Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN), and the CRITIC method (Criteria Importance Through Intercriteria Correlation). To address the dynamic nature of traveler preferences in hotel selection, the study employs a comprehensive set of criteria encompassing aspects such as location proximity, amenities, pricing, customer reviews, environmental impact, safety, booking flexibility, and cultural experiences. The CRITIC method is used to determine the importance of each criterion by assessing intercriteria correlations. AROMAN is employed for the systematic evaluation of alternatives, considering their additive relationships and providing a weighted assessment. WASPAS further analyzes the results obtained from AROMAN, incorporating both positive and negative aspects for a comprehensive evaluation. The integration of C-IFS enhances the model’s ability to manage uncertainty and imprecision in the decision-making process. Through a case study, we demonstrate the effectiveness of this integrated approach, offering decision-makers valuable insights for selecting the most suitable hotel option in alignment with the diverse preferences of contemporary travelers. This research contributes to the evolving field of decision science by showcasing the practical applicability of these methodologies within a C-IFS framework for complex decision scenarios.
... In addition, universities are also confronted with the challenge of maintaining existing facilities to ensure they remain in optimal condition. It is not enough to simply build new facilities; regular maintenance and Study by [2], revealed that the TOPSIS is used in decision-making by assessing how near an alternative is to the most favorable ideal solution while also considering its distance from the least favorable ideal solution. Applying the TOPSIS method can optimize facility development based on students' preferences and needs. ...
This research aims to prioritize campus facilities for development based on student preferences using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Recognizing the critical role of facilities in enhancing student success and retention, this study evaluates key criteria such as needs, comfort, current conditions, accessibility, and frequency of use. Data were collected through a random sampling survey involving 98 active students, determined using Slovin's formula with a 10% margin of error. The analysis identifies WiFi as the top priority for improvement, followed by toilets and lifts. This research highlights how TOPSIS has been applied effectively in decision-making processes within education and facility management, offering a structured approach for optimizing resource allocation.
... In the SAW method, the value of each alternative is calculated by adding up the results of multiplying the criteria weights by the normalized values, so the process is easier than other methods, such as AHP or TOPSIS (K. Paul Yoon, 1995). The SAW method allows fast data normalization and can handle various criteria without complex calculations (Triantaphyllou, 2000). ...
The increase in population is in line with the increase in resource use, including the need for land as a space for human activities to meet their needs. Land conversion, primarily agricultural land, into non-agricultural land can reduce the ability of land ecosystems to provide food. This research aims to assess the performance of ecosystem services for providing rice food in Malang Regency. The study used the Simple Additive Weighting (SAW) method, a simple weighting and scoring method of land use parameters, landform ecoregions, natural vegetation types, soil types, and rainfall to determine ecosystem services for food provision. The results showed that the Malang Regency area consists of 5 classes of Ecosystem Service Performance Index (ESPI) for rice food providers, including Very High, High, Medium, Low, and Very Low. The Medium class is the ESPI class with the highest area of 117,452.85 hectares or 34% of the total area. Followed by Low ESPI class 99,980.31 hectares (29%), High ESPI class 90,742.14 hectares (26%), Very Low ESPI class 19,191.28 hectares (6%), and Very High ESPI class 17,442.59 (5%).
... There are many methods for solving MCDM problems and the choice is made based on the nature of the problem and the level of complexity of the decision-making process [19]. In [20], the authors divided MCDM problems into two general sub-categories: In [21], Ilbahar et al. conducted a state-of-the-art review about MADM methods used throughout the renewable energy literature for the following purposes: evaluation of renewable energy sources, evaluation of renewable energy technologies, evaluation of renewable energy facility location, evaluation of renewable energy projects or investments, and design of renewable energy systems. The review concluded that the MADM methods most commonly used, including their various combinations, for solving the renewable energy problems mentioned before are Analytic Hierarchy Process (AHP) [22,23], Analytic Network Process (ANP) [22,23], Elimination Et Choix Traduisant la Realité (ELECTRE) [22,24] and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [22,25]. ...
The growing energy demand of the industrial sector and the need for sustainable solutions highlight the importance of efficient decision making in solar photovoltaic (PV) implementation. Selecting optimal PV configuration is complex due to the interdependent technical, economic, environmental, and social factors involved. This study introduces an integrated decision-making method combining a morphological matrix and fuzzy TOPSIS to systematically select and rank optimal PV system configurations for manufacturing firms. While the morphological matrix exhaustively examines possible design solutions based on sensing, smart, sustainable, and social (S4) attributes, the fuzzy TOPSIS method ranks the alternatives by handling uncertainty in decision making. A case study conducted in a Mexican manufacturing company validates the methodology’s effectiveness. The optimal PV configuration identified comprehensively addresses operational and sustainability criteria, covering all lifecycle stages. This approach demonstrates quantitative superiority and greater robustness compared to existing fuzzy TOPSIS-based methods for solar PV applications. The findings highlight the practical value of data-driven, multi-criteria decision making for industrial solar energy adoption, enhancing project feasibility, cost efficiency, and environmental compliance. Future research will incorporate discrete event simulation (DES) to further refine energy consumption strategies in manufacturing.
... TOPSIS ranks alternatives based on their proximity to an ideal solution and furthest from the negative ideal solution, providing a straightforward ranking mechanism useful in scenarios where clear distinctions between ideal and non-ideal solutions are crucial [35]. Recent articles such as [36] address the critical issue of flood risk assessment in coastal cities. ...
Purpose
This study aims to identify and rank the key risk factors associated with the Zika virus by leveraging a novel multi-criteria decision-making (MCDM) framework based on type-2 heptagonal fuzzy sets. By integrating advanced aggregation operators, the framework effectively addresses uncertainties in expert assessments and enhances decision-making reliability.
Methods
A robust MCDM approach was developed using type-2 heptagonal fuzzy sets, which provide a more nuanced representation of uncertainty compared to traditional fuzzy models. These sets were selected due to their superior ability to handle vague, imprecise, and subjective expert judgments, common challenges in epidemiological risk assessments. Arithmetic and geometric aggregation operators were employed to process fuzzy data effectively. To ensure comprehensive and reliable rankings, the framework incorporated both outranking methods and distance-based approaches, specifically TOPSIS and WASPAS. A sensitivity analysis was conducted to validate the stability of the rankings under varying conditions.
Results
The proposed framework identified (unprotected sexual activity) as the most critical risk factor with a score of 0.6717, followed by (blood transfusions) at 0.5783, (pregnancy) at 0.5753, (mosquito bites) at 0.4917, and (travel to endemic areas) at 0.4726. The rankings remained consistent across different MCDM methods (TOPSIS and WASPAS), demonstrating the robustness of the proposed approach. Pearson correlation analysis confirmed a strong agreement between methods, with correlation coefficients, reinforcing the reliability of the model.
Conclusion
This study introduces an advanced decision-support system for healthcare professionals to systematically identify and prioritize Zika virus risk factors. By leveraging type-2 heptagonal fuzzy sets, the framework effectively captures and processes uncertainty stemming from incomplete epidemiological data, imprecise expert assessments, and subjective linguistic evaluations. The consistency of rankings across multiple MCDM methods, along with sensitivity analysis confirming their stability, demonstrates the model’s reliability. These findings provide a scientifically grounded tool for improving risk analysis and strategic public health interventions.
... Burada maksimum değer Vi, en fazla tercih edilen alternatif ise Ai ile gösterilir. SAW yönteminde tüm kriterlerin mukayese edilebilme özelliğine sahip sayısal verilerden oluşmasına dikkat edilmelidir ve bu gereklilik yöntemin uygulanabilmesi için çok önemlidir (Yoon, 1995). Sonuç olarak; SAW yönteminde alternatif seçimi, karar vericilerin değerlendirilmeleri sonucunda oluşan karar matrisinin normalizasyon işleminin gerçekleştirilerek yine karar vericiler aracılığıyla belirlenen ve toplamları 1 olan faktör ağırlıklarıyla çarpılması ve alternatiflerin toplam puanlarının toplanarak maksimum puana sahip alternatifin seçilmesi şeklinde gerçekleşmektedir (Demircioğlu, 2010). ...
... When there are several good choices and crucial factors need to be examined to choose the best one, Hwang and Yoon [57] first proposed it in 1981. According to TOPSIS, the chosen action should stay as near to the ideal solution (the best possible result) as is practically practicable while avoiding the negative-ideal solution (the worst possible consequence) to the best of our abilities [58][59][60][61]. According to TOPSIS, the optimal choice should be located as far from the negative-ideal solution (NIS) and as close to the positive-ideal solution (PIS) as is practically possible. ...
Background: Because of their enhanced thermophysical characteristics, namely greater thermal
conductivity, viscosity control, and long-term stability than traditional nanofluids, hybrid
nanofluids drew interest. Such properties make them suitable candidates for many industrial
applications such as solar systems and thermal management. However, knowing the thermo-
physical properties of these materials accurately is difficult because of the complexities of
nanoparticles and the interaction with the base fluid. This paper utilizes machine learning
methods to predict the thermophysical properties of water/ethylene glycol mixture-based hybrid
nanofluids containing reduced silver-graphene oxide.
Methodology: This study aimed to predict Viscosity (DV), Thermal Conductivity (TC) and
Density (D) by three machine learning algorithms including multiple linear regression (MLR),
Multiple Polynomial Regression (MPR) and Gaussian Process Regression (GPR). A 5 × 28 dataset
was used for training and testing the network, with 80 % of the data used for training the network
and 20 % for testing the network. Evaluating the performance of algorithms is based on the
evaluation indices of Correlation coefficient (R), Root Mean Square Error (RMSE), Mean Absolute
Error (MAE) and Standard Deviation (STD). In addition, optimization is done by the Non-
dominated Sorting Genetic Algorithm-II (NSGA-II) algorithm and the impact results of different
mutation and combination rates are examined.
Results: The MPR algorithm yielded the lowest MoD values (0.07 % and 0.06 %) and the highest
prediction accuracy among the models tested (R = 0.9999, RMSD = 2.726 × 10 4, STD =
0.0219). Furthermore, NSGA-II optimization results revealed that the temperature and concen-
tration of nanoparticles could effectively increase the thermal conductivity, while too high
concentration could also increase viscosity. Finally, through the TOPSIS method, the best point
was chosen giving a blend of ideal thermophysical properties. This signifies that machine lear-
ning methods can be successfully employed for the prediction and optimization of hybrid
nanofluid characteristics
... Application of PROMETHEE Method in Evaluation of Insurance Efficiency in Serbia. Revija za ekonomske in poslovne vede, Journal of Economic and Business Sciences, 10(1),[3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. DOI: https://doi.org/10.55707/eb.v10i1.121 ...
Istraživanje kvaliteta aktive bankarskog sektora je vrlo izazovno, kontinuirano aktuelno, složeno i značajno. Kvalitet aktive u značajnoj meri utiče na ukupne performanse bankarskog sektora. Otuda je neophodno što efikasnije upravljati kvalitetom aktive bankarskog sektora. Imajući to u vidu, uovom radu se analizira dinamika kvaliteta aktive bankarskog sektora u Srbiji na bazi LMAW-DNMA
metoda. Prema dobijenim rezultatima LMAW-DNMA metoda najbolji kvalitet aktive bankarskog sektora u Srbiji ostvaren je u 2013. godine, zatim u 2011, 2016, 2012 i 2014. godini. Na nepovoljan kvalitet aktive bankarskog sektora u Srbiji u periodu 2019-2021. godine uticala je pandemija korona virusa Covid-19, tako što je prouzrokovala pad privrednih, a time i kreditnih aktivnosti, i u velikoj meri
prolongiranje otplate kreditnih obaveza. U 2022. i 2023. godini zabeleženo je neznatno poboljšanje kvaliteta aktive bankarskog sektora u Srbiji. Dakle, neophodno je, između ostalog, što efikasnije upravljati.
Investigating the quality of banking sector assets is very challenging, continuously adapting, complex, and significant. The quality of assets significantly affects the overall performance of the banking sector. Hence, it is necessary to manage the asset quality of the banking sector as
effectively as possible. Bearing that in mind, this paper analyzes the dynamics of asset quality in the banking sector in Serbia based on the LMAW-DNMA method. According to the results of the LMAW-DNMA method, the best asset quality of the banking sector in Serbia was achieved in 2013 and then in 2011, 2016, 2012, and 2014. The unfavorable quality of the assets of the banking sector in Serbia in the period 2019-2021 was affected by the COVID-19 pandemic by causing a decline
in economic and thus credit activities, and to a large extent prolonging the repayment of credit obligations. In 2022 and 2023, a slight improvement in the quality of banking sector assets in Serbia was recorded. Therefore, it is necessary, among other things, to manage credit risks as efficiently as possible and, consequently, to carry out an adequate distribution of available loans to the economy, sectors, and the population to achieve the target quality of assets of the banking sector in Serbia.
... TOPSIS is a multi-criteria decision-making (MCDM) technique that was initially proposed by (Yoon and Hwang, 1995). This method aims to minimize the Euclidean distance between the decision alternatives and the ideal state, while simultaneously maximizing their Euclidean ...
A B S T R A C T
The escalating challenge of unsustainable urban development worldwide has precipitated changes in land usage,
contributing to increased impermeability of the urban landscape. This phenomenon exacerbates urban runoff, a
critical environmental concern. In response, Low Impact Development (LID) techniques, recognized for their
environmental efficacy, have emerged as pivotal in mitigating urban runoff. However, transforming the hydrological dynamics of urban watersheds into a more sustainable state necessitates substantial financial commitments from relevant authorities. Consequently, strategic LID planning becomes essential to maximize
effectiveness while minimizing costs. This research introduces a novel, hybrid modeling strategy that integrates
the Storm Water Management Model (SWMM) with the Multi-Objective Evolutionary Algorithm by Decomposition (MOEA/D) optimization algorithm. This approach aims to concurrently minimize runoff volume, peak flow
rate, and implementation expenses. Focusing on a segment of Tehran Municipality’s urban stormwater system in
District 11, the study evaluates four distinct LID scenarios. These scenarios encompass various configurations of
Rain Barrels (RB), Bioretention Cells (BC), Green Roofs (GR), and Porous Pavements (PP). Utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for comparative analysis, the study
results identify the most efficacious scenario, S2_1, including RB and BC, which achieves a 19.34% reduction in
runoff volume and a 46.53 % decrease in peak flow rate, all at the implementation cost of 123,169 USD. A close
second, scenario S3_1 incorporating RB and PP, demonstrates a 17 % and 46.55 % reduction in runoff volume
and peak flow at an expenditure of 107,017 USD, respectively. The proposed SWMM-MOEA/D model, in
conjunction with TOPSIS, presents a valuable tool for LID planning and optimization, offering decision-makers
and relevant entities a pragmatic approach to address the challenges of urban runoff management.
... Application of PROMETHEE Method in Evaluation of Insurance Efficiency in Serbia. Revija za ekonomske in poslovne vede, Journal of Economic and Business Sciences, 10(1),[3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. DOI: https://doi.org/10.55707/eb.v10i1.121 ...
Investigating the quality of banking sector assets is very challenging, continuously adapting, complex, and significant. The quality of assets significantly affects the overall performance of the banking sector. Hence, it is necessary to manage the asset quality of the banking sector as effectively as possible. Bearing that in mind, this paper analyzes the dynamics of asset quality in the banking sector in Serbia based on the LMAW-DNMA method. According to the results of the LMAW-DNMA method, the best asset quality of the banking sector in Serbia was achieved in 2013 and then in 2011, 2016, 2012, and 2014. The unfavorable quality of the assets of the banking sector in Serbia in the period 2019-2021 was affected by the COVID-19 pandemic by causing a decline in economic and thus credit activities, and to a large extent prolonging the repayment of credit obligations. In 2022 and 2023, a slight improvement in the quality of banking sector assets in Serbia was recorded. Therefore, it is necessary, among other things, to manage credit risks as efficiently as possible and, consequently, to carry out an adequate distribution of available loans to the economy, sectors, and the population to achieve the target quality of assets of the banking sector in Serbia.
This study investigates how virtual reality (VR) can transform safety training, risk management, and auditing techniques in warehouse environments, using a mixed-methods approach to deliver practical guidance for industry and VR developers. The analysis applies four phases. The first phase involves observational studies to identify current safety practices, risk management strategies, and audit techniques. Semi-structured interviews with 15 safety experts for empathy mapping and the Delphi Technique with 10 experts to populate the 9-Window framework, assessing training needs and VR integration. The third phase utilizes critical thinking (CT) questions to analyze VR features, and the fourth phase applies the Analytic Hierarchy Process (AHP) to rank VR feature priorities based on their impact and feasibility. Observation findings indicate significant gaps in current safety practices and safety training. Semi-structured interviews and CT discussions demonstrate that VR training significantly enhances safety skills and auditing capabilities and fosters proactive risk management. Immersive VR allows trainees to utilize VR features, such as simulation of misplaced items, risk identification, voice instructions, interaction, and navigation, which were emphasized as crucial components. Furthermore, AHP results show that simulation realism and immersive interaction are the most critical factors for effective VR safety training. Overall, the study highlights VR training as a valuable tool for designers and users in enhancing warehouse safety management, auditing skills, and risk management practices. However, limitations include the need for broader risk scenario training in VR. Future research should quantify training effectiveness and compare it with conventional methods.
Bài viết này sử dụng mô hình tích hợp kết hợp phân tích phân cấp mờ (Fuzzy-AHP) và kỹ thuật ưu tiên tương đồng với giải pháp lý tưởng (TOPSIS) nhằm cung cấp một khung đánh giá và xếp hạng các điểm đến du lịch mạo hiểm tiềm năng. Nghiên cứu lựa chọn Hà Giang, một tỉnh miền núi Đông Bắc Việt Nam, nổi tiếng với địa hình hiểm trở và tiềm năng du lịch mạo hiểm đa dạng. Dữ liệu được thu thập từ 35 chuyên gia thông qua khảo sát chuyên sâu và được phân tích bằng quy trình Fuzzy-AHP-TOPSIS. Đỉnh Chiêu Lầu Thi được xác định là điểm du lịch mạo hiểm hấp dẫn nhất tại Hà Giang theo kết quả phân tích. Nghiên cứu này góp phần đánh giá điểm đến du lịch mạo hiểm, bằng cách cung cấp một phương pháp luận có cấu trúc chặt chẽ; đồng thời đưa ra các khuyến nghị có giá trị thực tiễn cho các nhà quản lý du lịch và các bên liên quan, hỗ trợ việc hoạch định chiến lược phát triển du lịch mạo hiểm bền vững, không chỉ tại Hà Giang mà còn cho các điểm đến du lịch tương đồng khác.
Portfolio rebalancing is a critical aspect of investment management, ensuring that an investment portfolio remains aligned with an investor's objectives over time. Due to changes in the economic environment and company policies, the fundamental situation of companies evolves. This paper presents a multi-objective model for portfolio rebalancing based on the Constant Proportion Portfolio Insurance (CPPI) strategy, with the objectives of minimizing risk, minimizing transaction costs, and maximizing the portfolio’s fundamental criteria. The model incorporates interval uncertainty in parameters such as the price-to-earnings ratio and is reformulated using a robust optimization approach. A revised multi-choice goal programming method is applied to solve the model. The proposed method is evaluated in both bullish and bearish market cycles, as well as during a financial crisis, to ensure its robustness and performance across varying market conditions. The results show that, without rebalancing, the investor incurs greater losses during bearish markets. However, by implementing the proposed rebalancing strategy, the portfolio’s floor value is maintained, and the portfolio experiences only a slight decrease in value during market downturns. Additionally, by incorporating fundamental factors, the strategy leads to higher returns and lower risk in bullish markets compared to other strategies.
Hydrogen has garnered significant attention in recent decades as a crucial component of energy systems for a sustainable future, leading to a notable emphasis on improving the sustainability of hydrogen energy production systems. Among the different methods of hydrogen production, green hydrogen is regarded as the most desirable energy option for future generations. However, despite its advantages, the selection of the most suitable method for green hydrogen production involves a complex analysis. Given this complexity, it becomes essential to employ a systematic approach to evaluate and compare the different options effectively. To address this multifaceted decision-making challenge, a Multi-Attribute Decision-Making (MADM) framework can be invaluable. In this context, this paper adopts the Evaluation based on Distance from Average Solution (EDAS) approach, which is recognized for its practicality and robustness in assessing alternatives. Nonetheless, the implementation of the traditional EDAS method does have certain limitations, despite its ability to offer a systematic decision-making framework. The traditional EDAS method is not capable of handling decision matrices that simultaneously contain both quantitative values and qualitative evaluations. To address this limitation, this study presents a novel modification to the EDAS method that integrates pairwise qualitative and direct quantitative evaluations, aiming to propose a comprehensive technique that combines both attribute types and provides decision-makers with a unified framework for determining the most suitable option for green hydrogen production. The computational results of this modified method indicate that wind electrolysis emerges as the most suitable option for green hydrogen production. Additionally, a comparative analysis with other MADM techniques, alongside a thorough sensitivity analysis, underscores the robustness and reliability of the proposed framework. The implications of the modified EDAS framework extend beyond theoretical contributions; it offers a systematic approach for resource allocation and aligns with industry standards for sustainable green hydrogen production. By facilitating informed decision-making, this framework equips stakeholders with the tools necessary to advance sustainable energy solutions effectively.
A multi-objective linear programming problem addresses the complexities that arise in most practical decision-making scenarios. Such problems are crucial in various practical applications where multiple conflicting objectives must be optimized simultaneously. However, traditional optimization methods struggle to effectively manage uncertainty and vagueness. To address these shortcomings, hesitant fuzzy set theory was introduced. This theory allows decision-makers to express the uncertainty about the exact belongingness of an element in a set, accommodating imprecision and ambiguity. Additionally, the VIKOR method, which is a well-established multi-criteria decision-making technique, that has been used to identify a compromise solution among multiple conflicting objectives. In this study, we propose a bi-phase modified VIKOR method to solve multi-objective programming problems within hesitant fuzzy environment. The applicability and effectiveness of the developed methodology are demonstrated with a popular production planning problem. To validate results, the outcomes of the proposed methodology are compared with the various existing methods, highlighting the robustness and efficacy of the developed methodology.
This study introduces a novel Recency, Monetary, and Duration (RMD) model for customer classification in the hospitality industry. Using a hybrid approach that integrates data mining with multi-criteria decision-making techniques, this study aims to identify valuable customer segments and optimize marketing strategies. This research applies the K-means clustering algorithm to classify customers from a hotel in Iran based on RMD attributes. Cluster validation is performed using three internal indices, and hidden patterns are extracted through association rule mining. Customer segments are prioritized using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method and Customer Lifetime Value (CLV) analysis. The outcomes revealed six distinct customer clusters, identified as new customers; loyal customers; collective buying customers; potential customers; business customers, and lost customers. This study helps hotels to be aware of different types of customers with particular spending patterns, enabling hotels to tailor services and improve customer retention. It also provides managers with appropriate tools to allocate resources efficiently. This study extends the traditional Recency, Frequency, and Monetary (RFM) model by incorporating duration, an overlooked dimension of customer engagement. It is the first attempt to integrate data mining and multi-criteria decision-making for customer segmentation in Iran’s hospitality industry.
The preceding chapter adopts the perspective of matching agents, examining preference relationships through pairwise comparisons and subsequently outlining the corresponding decision-making framework. Nonetheless, as decision-making scenarios grow in complexity, agents increasingly express distinct expectations and demands across various dimensions.
This study evaluates green space suitability in İzmir’s Konak district using the analytic hierarchy process, machine learning, weighted linear combination, and the technique for order preference by similarity to ideal solution methods, integrated with geographic information systems. The approach enhances reliability in green space identification by ensuring consistent integration of weights determined by different methods. Machine learning enables dynamic adjustments to criterion weights, yielding the best results with the random forest algorithm. The analysis revealed that 75% of green spaces were sub-optimally located, with optimal zones in the western and northern regions. The technique for order preference by similarity to ideal solution methodology prioritized area ZGS_6 as the most suitable area, while ZGS_4 ranked lowest. This method supports efficient resource allocation and improves budgeting processes. Hence, the integration of multi-criteria decision-making and machine learning with geographic information systems enhances the planning of sustainable cities and offers critical insights to decision-makers who prioritize sustainability and livability.
This paper proposes a multi-criteria decision-making method based on CSOGRMILP and Borda-CoCoSo in a probabilistic hesitant fuzzy environment. In this method, we utilize a probabilistic hesitant fuzzy scoring function to process the probabilistic hesitant fuzzy information, obtaining a processed decision matrix. Then, based on the processed decision matrix, we propose the “Combined Subjective-Objective, Gray Relational Analysis, Mixed Integer Linear Programming” (CSOGRMILP) method to determine the weights of decision criteria. Next, an improved method called Borda-CoCoSo is proposed for ranking solutions based on the Borda rule modification of the Combined Comprise Solution (CoCoSo) method. Finally, a case study on the selection of degradable dynamic plastic products was used to validate the proposed method. In the comparative analysis, we compare the proposed method with traditional methods. This further validates the rationality of the Borda-CoCoSo method. Additionally, we compare CSOGRMILP with EWM (Entropy Weight Method), MEREC (MEthod based on the Removal Effects of Criteria), CRITIC (CRiteria Importance Through Inter-criteria Correlation), and ROSOSD (The Robustness, Correlation, and Standard Deviation). The comparison results indicate that CSOGRMILP demonstrates better stability (0.046) and the best consistency (96.43%).
This study introduces a novel Recency, Monetary, and Duration (RMD) model for customer classification in the hospitality industry. Using a hybrid approach that integrates data mining with multi-criteria decision-making techniques, the study aims to identify valuable customer segments and optimize marketing strategies.The research applies the K-means clustering algorithm to classify customers from a hotel in Iran based on RMD attributes. Cluster validation is performed using three internal indices, and hidden patterns are extracted through association rule mining. Customer segments are prioritized using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method and Customer Lifetime Value (CLV) analysis. The outcomes revealed six distinct customer clusters identified as New customers; Loyal customers; Collective Buying Customers; Potential customers; Business customers and Lost customers. This study helps hotels to know different types of customers with spending patterns which enable hotels to tailor services and improve customer retention and provides managers appropriate tools to allocate resources efficiently. This study extends the traditional Recency, Frequency, and Monetary (RFM) model by incorporating Duration, an overlooked dimension of customer engagement. It is the first attempt to integrate data mining and multi-criteria decision-making for customer segmentation in Iran’s hospitality industry.
div class="section abstract"> In this work, design optimization for the lightweight of the body frame of a commercial electric bus with the requirements of stiffness, strength and crashworthiness is presented. The technique for order preference by similarity to ideal solution (TOPSIS) is applied to calculate the components that have a great impact on the output response of the static modal model and the rear-end collision model. The thickness of the five components with the highest contribution in the two models is determined as the final design variable. Design of experiment (DOE) is carried out based on the Latin Hypercube sampling method, and then the surrogate models are fitted by the least squares regression (LSR) method based on the DOE sampling data. The error analysis of the surrogate model is carried out to determine whether it can replace the finite element (FE) model for optimization, then the optimization scheme for lightweight optimization of electric bus frame is implemented based on the algorithm of composite differential evolution for constrained evolutionary optimization (C2oDE). Comparing the optimization results with the initial values, it can be found that the mass of the electric bus body frame is reduced by 51.59kg with a reduction rate of 4.99%. Meanwhile, the energy absorption of the rear wall increases by 2.79%, the maximum intrusion is reduced by 0.36%, the intrusion velocity at the center of the rear wall of the electric bus body frame is reduced by 0.46%, the acceleration at the cabin center is reduced by 3.29%, and the crashworthiness performance of the electric bus body frame is also improved.
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Take-all disease, caused by the fungal pathogen Gaeumannomyces tritici, severely impacts the growth and grain yield of wheat. Identifying loci associated with disease resistance can be achieved through molecular methods, along with data on morphological traits and disease severity. This study analyzed 100 bread wheat genotypes using molecular markers (SSR, IRAP technique, and translocation wheat-rye) and agronomical traits to pinpoint loci related to resistance to take-all disease. In this research, we propose a new approach using TOPSIS method for identifying ideal genotypes with resistance to take-all disease and the best in point of other agronomic traits. Genotypes were grouped based on agronomical traits (yield and its components) observed in the field, as well as root weight characteristics, root lignin content, and disease severity. These groupings effectively distinguished between resistant and sensitive genotypes. Stepwise regression techniques unveiled significant loci linked to disease resistance and agronomical traits. The presence of common loci suggests a potential pleiotropic nature of disease resistance. Molecular analysis exposed interactive loci contributing to trait variations and disease resistance, indicating gene-by-gene interactions. Using the IRAP technique, a locus from the LTR retrotransposon marker (LTR14) showed a strong correlation with take-all disease resistance and agronomic traits. This marker can serve as an informative and promising candidate for marker-assisted selection in wheat breeding programs. The TOPSIS method assisted in identifying genotypes showing high yield and resistance to take-all disease.
Çok Kriterli Karar Verme (ÇKKV) yöntemleri farklı alan ve disiplinlerde başarıyla uygulanmaktadır. Ancak birçok çalışmada karar problemlerine uygun yöntem ve parametrelerin seçilmesi sorunu gündeme gelmektedir. Bu makalede, ÇKKV yöntemlerinin karşılaştırılması yapılmıştır. Yöntemlerden AHP, TOPSIS, VIKOR, Bulanık TOPSIS ve Bulanık VIKOR kullanılmıştır. Bu analizleri yapmak için COVID-19 sonrası değişimlerle mobilya işletmelerinin web siteleri değerlendirilmiştir. Uygulamada literatür taraması ve uzman görüşü sonucunda altı ana kriter olmak üzere toplam 31 kriter belirlenmiştir. AHP yönteminden kullanılan kriterlerin ağırlıklarını hesaplanmıştır. Daha sonra yöntemlerden elde edilen sonuçlara göre web sitelerinin sıralamasını elde edilmiştir. Sonra ise yöntemler klasik sonuçların sıralaması, ilişki testi, işlem karmaşıklığı ve alternatif sayısındaki değişiklik ile karşılaştırılmıştır. Sonuçlar, kullanılan tüm yaklaşımların web sitesi değerlendirmesinde uygun olduğunu göstermektedir. Fakat ilişki testinde yöntemlerin benzer sonuçlar çıktığı, hesaplama karmaşıklığında VIKOR daha iyi performans gösterdiği ve alternatif değişikliklerine uygunlukta ise bulanık TOPSIS yöntemi daha iyi performans gösterdiği gözlemlenmiştir.
Negative number/value plays an important role in expressing our preferences (i.e., temperature, economic growth, etc.). However, it has received different attention than positive references in the literature. On the other side, many of our decisions have a percentage of uncertainty and are often expressed as interval data. In this paper, the decision method used is the Simple Additive Weighting (SAW) method. This method was developed to be used when the data are of an interval nature. However, the conventional SAW method with interval data cannot deal with negative data. The critical question is, “What can we do when using the data set containing negative numbers in the SAW method with interval data”? This is the problem we wish to address in this chapter. Further, Salehi and Izadikhah (Decision Science Letters 3:225–236, 2014) extended the SAW technique using interval numbers. We use the Salehi and Izadikhah algorithm to calculate the alternative scores, but we change the procedure of calculating the conventional arithmetic operations to the arithmetic operations proposed by Yamanaka and Oishi (RIMS Kokyuroku Bessatsu B54:71–98, 2015). The results have demonstrated our model to be both robust and efficient.
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