682 research outputs found

    An integrated MCDM approach to evaluate public transportation systems in Tehran

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    Public transportation is one of the most important systems in transportation, especially in big and crowded cities. As a result, evaluation of public transportation systems is a strategic decision-making problem for both private and public sections. In this paper, the problem of public transportation passengers in Tehran is addressed and their satisfaction levels are assessed by using passenger satisfaction survey. An integrated MCDM approach is proposed for evaluation of public transportation systems based on Delphi method, group analytic hierarchy process (GAHP) and preference ranking organization method for enrichment of evaluations (PROMETHEE). The proposed model provides more reliable and realistic results and introduces directions for future improvements of public transportation service quality. A sensitivity analysis is applied to investigate the influence of criteria weights on the decision making problem. As a conclusion, the most important public transportation systems in Tehran orderly are: metro, taxi, BRT, bus and van. Therefore, Tehran Municipality and policy makers should encourage and support the previously mentioned systems

    Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences

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    Mathematical fuzzy logic (MFL) specifically targets many-valued logic and has significantly contributed to the logical foundations of fuzzy set theory (FST). It explores the computational and philosophical rationale behind the uncertainty due to imprecision in the backdrop of traditional mathematical logic. Since uncertainty is present in almost every real-world application, it is essential to develop novel approaches and tools for efficient processing. This book is the collection of the publications in the Special Issue “Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences”, which aims to cover theoretical and practical aspects of MFL and FST. Specifically, this book addresses several problems, such as:- Industrial optimization problems- Multi-criteria decision-making- Financial forecasting problems- Image processing- Educational data mining- Explainable artificial intelligence, etc

    Uncertain Multi-Criteria Optimization Problems

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    Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

    COMBINING THE SUITABILITY-FEASIBILITY-ACCEPTABILITY (SFA) STRATEGY WITH THE MCDM APPROACH

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    Suitability-Feasibility-Acceptability (SFA) is a fundamental tool for the development and selection of strategy. Any type of decision-making problem can be resolved by Multiple Criteria Decision Making (MCDM) methods. In this research, we explore the complexity of determining the proper goal market for the Chilean fish market. This study proposed a combined approach of SFA with MCDM methods in a real case study. The proposed structure helps to assign the best market for Chilean export fish to West Asia. Three countries (Saudi Arabia, the United Arab Emirates, and Oman) are selected as a target market in this region, and then related criteria are obtained from various sources. In order to develop a new market for the Chilean fishery industry, five major criteria, including the potential of a target market, region's economic attractiveness, consumption of the seafood, location, cost of transportation, and country risks, were selected based on the SFA framework. Calculating the criteria weights is performed by the Best-Worst (BWM) method, and ordering the alternatives is operated by Measurement Alternatives and Ranking according to compromise Solution (MARCOS) methods. The results showed that Oman is the best destination (importer) for the Chilean fish market (Salmon fish as the case)

    Review on ship onboard machinery maintenance strategy selection using multi-criteria optimization

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    Abstract: Marine shipping is an important aspect of the transportation system in Canada. It is estimated that 70-80% of items that we are surrounded by and use daily are brought by ships. Canadian businesses need to sell to the world and ships carries their products abroad. For people that live in Canada’s island or northern communities, marine shipping is often the only source they have for essentials. It is estimated that marine shipping directly contributes about $3 billion annually to Canada’s GDP through employment and other impacts. In a marine ship system, safety and reliability are very important considerations. The various system elements must be properly maintained and organizations are now looking to maintenance optimization to achieve optimum safety, machinery reliability and reduced costs. Modern day maintenance optimization is a decision-making problem which need to satisfy multiple and conflicting criteria. Multi-Criteria Optimization (MCO) techniques have been used in maintenance optimization. Two main classes of maintenance MCO problems have been identified as strategy selection and interval optimization. In marine ships, maintenance strategy selection is a complex decision-making problem that has become ever more challenging to address and is accompanied by diverse constraints and economic considerations. Each maintenance strategy has its own characteristics, importance and drawbacks. The use of inappropriate maintenance strategy affects the safety of a ship, crew, machinery reliability, maintenance cost etc. MCO techniques have been used in selecting optimal maintenance strategy for ship onboard machinery.Communication présentée lors du congrès international tenu conjointement par Canadian Society for Mechanical Engineering (CSME) et Computational Fluid Dynamics Society of Canada (CFD Canada), à l’Université de Sherbrooke (Québec), du 28 au 31 mai 2023

    An overview of fuzzy techniques in supply chain management: bibliometrics, methodologies, applications and future directions

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    Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM

    Logistic autonomous vehicles assessment using decision support model under spherical fuzzy set integrated Choquet Integral approach

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    Autonomous vehicles (AVs) are the newest products in the intelligent transportation system that can move around with minimal human intervention. These products continue their path with all kinds of sensors with different parts. Effective use of these technologies in the logistics industry can create a competitive advantage. Nowadays, there are many AVs, some of which are superior to others in terms of build quality, variety of features, and design. Choosing an efficient, optimal, and reliable vehicle is one of the most important challenges in logistics planning. Therefore, choosing an AV based on a series of criteria can be considered a multi-criteria decision-making (MCDM) problem. Due to the complication of decision-making issues, criteria are usually not independent of each other and there are relationships between them. Therefore, this study develop an extended MCDM framework based on Choquet integral (CI) under group decision-making with a Spherical fuzzy set (SFS) for assessing logistics AVs. The CI technique is expanded with SFS to increase the power of CI. Furthermore, the combination of CI with SFS leads to greater freedom for decision makers to express opinions and use three independent membership functions. Accordingly, the interactions between the criteria are considered and the skepticism and uncertainty present during the decision are controlled. The proposed approach is implemented in selecting the best AVs in the logistics industry, and the results are compared with Pythagorean fuzzy CI and Intuitionistic fuzzy CI. Moreover, sensitivity analysis is done by changing the weights and creating different scenarios to confirm and check the robustness of the proposed approach results. The results indicate the suggested approach's efficiency and the ranking's stability in different scenarios
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