Multi-Criteria Decision-Making Model for Evaluating Safety of Road Sections

Stević, Željko; Subotić, Marko; Softić, Edis; Božić, Branko

doi:10.56578/jimd010201

Cited by 12 publications

(5 citation statements)

References 16 publications

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“…In this section of the study, we perform an extension of the SWARA [45] method with fuzzy-rough numbers, which has large applications in decision-making processes. This method, through more than a decade of use, is extended with various theories, such as rough [46], interval rough [47], fuzzy [48,49], and neutrosophic [50]. However, in the literature, we did not find the fuzzy-rough SWARA method, so we decided to develop it.…”

Section: A Novel Fuzzy-rough Swara Methodsmentioning

confidence: 99%

A Fuzzy–Rough MCDM Approach for Selecting Green Suppliers in the Furniture Manufacturing Industry: A Case Study of Eco-Friendly Material Production

Zhou

Štilić²,

Stević

et al. 2023

Sustainability

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Green supplier selection is always one of the most important challenges in all of supply chain management, especially for production companies. The purpose is to have reliable suppliers which can fulfill all requests and be flexible in any supply chain stage. The aim of this paper is to create an adequate and strong MCDM (multicriteria decision making) model for the evaluation and selection of suppliers in a real environment. The main contribution of this study is proposing a novel fuzzy–rough MCDM model containing extension stepwise weight assessment ratio analysis (SWARA) and additive ratio assessment (ARAS) methods with fuzzy–rough numbers (FRN). The integrated FRN SWARA–FRN ARAS model was implemented in a case study of eco-friendly material production. The FRN SWARA method was used to calculate the weights of 10 green criteria, while using FRN ARAS, 6 suppliers were evaluated. The results of the applied model show that supplier S3 received the highest ranking, followed by supplier S2, while supplier S5 performed the poorest. In order to verify the strengths of the developed fuzzy–rough approach, we created a comparative analysis, sensitivity analysis, and dynamic matrix, which confirm the robustness of our model.

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Section: A Novel Fuzzy-rough Swara Methodsmentioning

confidence: 99%

A Fuzzy–Rough MCDM Approach for Selecting Green Suppliers in the Furniture Manufacturing Industry: A Case Study of Eco-Friendly Material Production

Zhou

Štilić²,

Stević

et al. 2023

Sustainability

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show abstract

“…These studies include the use of deep learning and edge cloud computing for risk assessment in China's international trade and investment [64], the MCDM model for evaluating road section safety [65], and the application of interval-valued picture fuzzy uncertain linguistic Dombi operators in industrial fund selection [66]. These studies demonstrate a variety of approaches to risk management and decision making in a variety of contexts.…”

Section: Literature Reviewmentioning

confidence: 99%

Advancing Sustainable Urban Development: Navigating Complexity with Spherical Fuzzy Decision Making

Anjum,

Min,

Sharma

et al. 2024

Symmetry

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This study explores the complexities of urban planning and addresses major issues by carefully weighing four options for smart city technology, community-based development, green infrastructure investment, and transit-oriented development. Unlike traditional evaluations, our study applies the novel SWARA-WASPAS model to spherical fuzzy sets (SFSs), thus identifying and navigating the uncertainty present in decision making. This methodological approach improves the accuracy of our assessment by providing detailed information about the advantages and disadvantages of each option. Our study offers useful insights for urban policymakers and planners using carefully weighted criteria and employing a methodical ranking procedure. The aim is to provide insights for decisions that promote equity, environmental consciousness, resilience, and symmetry in urban environments. The application of the SWARA-WASPAS approach not only advances the field but also provides a strong basis for informed decision making. This improves the accuracy of our evaluations and provides detailed insights into each option’s pros and cons. Our study uses weighted criteria and systematic ranking to advise urban policymakers and planners. Our main goal is to help urban populations make resilient, environmentally responsible, equitable, and symmetrical decisions. Our research aims to further the conversation on sustainable urban development by offering a framework based on data that addresses the difficulties associated with dynamic urban environments. In the end, we want our humanized viewpoint to speak to a wider audience and inspire a shared dedication to creating cities that flourish in the face of changing urban environments.

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“…In MCDM methodology, sensitivity analysis is a matter of the degree of impact of a certain input or parameter change on the final results [16,17]. Frequently, attempts have been made to measure the effect of changing the weight coefficients of the criteria on the sensitivity of the ranking.…”

Section: Introductionmentioning

confidence: 99%

Interpreting the Determinants of Sensitivity in MCDM Methods with a New Perspective: An Application on E-Scooter Selection with the PROBID Method

Baydaş,

Kavacık,

Wang

2024

Spec. Eng. Man. Sci.

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It is not a desirable situation when input parameters excessively affect the results of a system as well as imply unwarranted drift and inefficiency. This situation, which expresses dependence or sensitivity to inputs, is also considered a problem in the multi-criteria decision-making (MCDM) methodology family, which has more than 200 members. A newly produced MCDM method is first subjected to sensitivity tests. MCDM methods are generally evaluated for their sensitivity to weighting methods. Sensitivity is affected by many different parameters such as data, normalization, fundamental equation, and distance type. The common methodical approach for sensitivity analysis is to check whether the best alternative changes with the alteration of weight coefficients. It is problematic to identify sensitivity only in the situation where the ranking position of the best alternative changes. In this study, the sensitivity of the entire ranking is based on a holistic view. Moreover, in the classical method, there is no reference point for sensitivity. Each different MCDM result is compared to each other and it is claimed that the method that produces rankings that are significantly different from the others is poor. We reinterpret sensitivity using the relationship between dynamic MCDM-based performance and static price towards the selection of an environmentally friendly, traffic-saving performance electric scooter. Two PROBID variants as well as the CODAS method are used in this study to deepen the accuracy in the comparison. Additionally, how four types of weighting methods and six types of normalization types affected MCDM sensitivity is measured with a different statistical framework. The finding from a total of 72 different MCDM rankings is striking: If the sensitivity of an MCDM method is generally high, the correlation between that MCDM method and the external anchor (price) is low. Conversely, if sentiment is low, a high correlation with price results. These matching patterns are a unique discovery of this work.

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Multi-Criteria Decision-Making Model for Evaluating Safety of Road Sections

Cited by 12 publications

References 16 publications

A Fuzzy–Rough MCDM Approach for Selecting Green Suppliers in the Furniture Manufacturing Industry: A Case Study of Eco-Friendly Material Production

A Fuzzy–Rough MCDM Approach for Selecting Green Suppliers in the Furniture Manufacturing Industry: A Case Study of Eco-Friendly Material Production

Advancing Sustainable Urban Development: Navigating Complexity with Spherical Fuzzy Decision Making

Interpreting the Determinants of Sensitivity in MCDM Methods with a New Perspective: An Application on E-Scooter Selection with the PROBID Method

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