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Many researchers generalize classical multi-criteria decision-making (MCDM) methods under fuzzy environment into fuzzy multi-criteria decision-making (FMCDM) for solving decision-making problems, such as the approaches of Chen, Liang, Raj and Kumar, Wang, and Wang et al. However, some problems occurred in the approaches above. For instance, the intersection of fuzzy numbers is a null set, the calculation for pooled fuzzy numbers is complex work, or the criteria values of anti-ideal/ideal solutions or lower/upper boundaries may not exist in feasible alternatives. In addition, there are too many computation steps to be realized and utilized for decision-makers. Recently, Wang proposed a method-associating technique for order preference by similarity to ideal solution (TOPSIS) with a relative preference relation to solve the above drawbacks of FMCDM. Wang resolved most of the problems with the above approaches, but we still desired to develop a method that was simpler than Wang's on computation. Therefore, we proposed an FMCDM method applying fuzzy similarities between evaluation alternatives and extreme solutions in this paper. The fuzzy similarities between evaluation alternatives and extreme solutions are based on a similarity relation between two fuzzy numbers, and this similarity relation was converted from Lee's extended preference relation. With the fuzzy similarities between evaluation alternatives and extreme solutions, alternative performance indices are easily yielded and then FMCDM are easily and efficiently finished in practice. Furthermore, the computation steps of FMCDM were simplified and reduced through the fuzzy similarities. Furthermore, we compared the proposed method with other methods including Wang's to demonstrate the feasibility and rationality of the method.
This edited book discusses creative and recent developments of fuzzy systems and its real-life applications of multiple criteria decision making. Keeping on the existing fuzzy sets and recent developed fuzzy sets, viz., intuitionistic fuzzy, Pythagorean fuzzy, Fermatean fuzzy, Hesitant fuzzy and multiple criteria decision approaches, this book is committed to probing the soft computing techniques and fuzzy multiple criteria decision making in favour of fuzzy intelligent system and business analytics. It also addresses novel development of fuzzy set theory as well as real-life applications of fuzzy systems. It presents challenging and useful real-world applications based on problems of decision making in various fields. The modelling and solution procedures of such real-world problems will be provided concisely although all topics start with a more developed resolution. The contributory chapters will be based on the vast research experiences of the authors in real-world decision-making problems. This book provides readers with a valuable conspectus of several decision-making problems as a reference for researchers and industrial practitioners in this field. This book will broadly cover recent development of fuzzy systems and its applications of multiple criteria decision making in the areas of management and production, manufacturing management, selections problems, group decision making, transportation and logistics, inventory control systems and interval technique/fuzzy technique (uncertainty) of the above mentioned areas.
This work examines all the fuzzy multicriteria methods recently developed, such as fuzzy AHP, fuzzy TOPSIS, interactive fuzzy multiobjective stochastic linear programming, fuzzy multiobjective dynamic programming, grey fuzzy multiobjective optimization, fuzzy multiobjective geometric programming, and more. Each of the 22 chapters includes practical applications along with new developments/results. This book may be used as a textbook in graduate operations research, industrial engineering, and economics courses. It will also be an excellent resource, providing new suggestions and directions for further research, for computer programmers, mathematicians, and scientists in a variety of disciplines where multicriteria decision making is needed.
Authored by a leading expert in the field, this book introduces an innovative methodology that harnesses the power of fuzzy logic to enhance decision-making in multi-attribute scenarios. In a world of complexity and uncertainty, effective decision-making is paramount. Springer proudly presents a cutting-edge publication that revolutionizes decision analysis: "Fuzzy Decision Analysis: Multi-attribute Decision-Making Approach." This book stands at the forefront of decision analysis, introducing the integration of fuzzy logic into multi-attribute decision-making. It is a transformative journey into the realm of advanced decision analysis. It book not only equips you with the knowledge to comprehend the theoretical underpinnings but also empowers you to apply these insights in practical scenarios. This book serves as your indispensable companion. Its comprehensive coverage serves as a beacon, guiding you through the intricate maze of fuzzy logic and multi-attribute decision-making, ultimately empowering you to embrace innovation and master the art of making well-informed decisions in an ever-changing world.
A guide to the various models and methods to multicriteria decision-making in conditions of uncertainty presented in a systematic approach Multicriteria Decision-Making under Conditions of Uncertainty presents approaches that help to answer the fundamental questions at the center of all decision-making problems: "What to do?" and "How to do it?" The book explores methods of representing and handling diverse manifestations of the uncertainty factor and a multicriteria nature of problems that can arise in system design, planning, operation, and control. The authors—noted experts on the topic—and their book covers essential questions, including notions and fundamental concepts of fuzzy sets, models and methods of multiobjective as well as multiattribute decision-making, the classical approach to dealing with uncertainty of information and its generalization for analyzing multicriteria problems in condition of uncertainty, and more. This comprehensive book contains information on "harmonious solutions" in multiobjective problem-solving (analyzing “i>X, F> models), construction and analysis of “i>X, R/i” models, results aimed at generating robust solutions in analyzing multicriteria problems under uncertainty, and more. In addition, the book includes illustrative examples of various applications, including real-world case studies related to the authors’ various industrial projects. This important resource: Explains the design and processing aspect of fuzzy sets, including construction of membership functions, fuzzy numbers, fuzzy relations, aggregation operations, and fuzzy sets transformations Describes models of multiobjective decision-making (“i>X. M/i” models), their analysis on the basis of using the Bellman-Zadeh approach to decision-making in a fuzzy environment, and their diverse applications, including multicriteria allocation of resources Investigates models of multiattribute decision-making (“i>X, R/i” models) and their analysis on the basis of the construction and processing of fuzzy preference relations as well as demonstrating their applications to solve diverse classes of multiattribute problems Explores notions of payoff matrices and fuzzy-set-based generalization and modification of the classic approach to decision-making under conditions of uncertainty to generate robust solutions in analyzing multicriteria problems Written for students, researchers and practitioners in disciplines in which decision-making is of paramount relevance, Multicriteria Decision-Making under Conditions of Uncertainty presents a systematic and current approach that encompasses a range of models and methods as well as new applications.
Using numerical examples to illustrate their concepts and results, this book examines recently developed fuzzy multi-criteria methods, such as Intuitionistic Fuzzy TOPSIS, Intuitionistic Fuzzy TOPSIS & DEA-AHP, Intuitionistic VIKOR, Pythagorean WASPAS, Pythagorean ENTROPI, Hesitant CBD, Hesitant MABAC, Triangular EDAS, Triangular PROMETHEE, q-Rung Orthopair COPRAS, and Fuzzy Type – 2 ELECTRE. Each chapter covers practical applications in addition to fresh developments and results. Given its structure and scope, the book can be used as a textbook in graduate courses on operations research and industrial engineering. It also offers a valuable resource for scientists working in a range of disciplines that require multi-criteria decision making.
This book is a printed edition of the Special Issue "Fuzzy Techniques for Decision Making" that was published in Symmetry
Fuzzy Multicriteria Decision-Making: Models, Algorithms and Applications addresses theoretical and practical gaps in considering uncertainty and multicriteria factors encountered in the design, planning, and control of complex systems. Including all prerequisite knowledge and augmenting some parts with a step-by-step explanation of more advanced concepts, the authors provide a systematic and comprehensive presentation of the concepts, design methodology, and detailed algorithms. These are supported by many numeric illustrations and a number of application scenarios to motivate the reader and make some abstract concepts more tangible. Fuzzy Multicriteria Decision-Making: Models, Algorithms and Applications will appeal to a wide audience of researchers and practitioners in disciplines where decision-making is paramount, including various branches of engineering, operations research, economics and management; it will also be of interest to graduate students and senior undergraduate students in courses such as decision making, management, risk management, operations research, numerical methods, and knowledge-based systems.
This book offers a comprehensive guide to the use of neutrosophic sets in multiple criteria decision making problems. It shows how neutrosophic sets, which have been developed as an extension of fuzzy and paraconsistent logic, can help in dealing with certain types of uncertainty that classical methods could not cope with. The chapters, written by well-known researchers, report on cutting-edge methodologies they have been developing and testing on a variety of engineering problems. The book is unique in its kind as it reports for the first time and in a comprehensive manner on the joint use of neutrosophic sets together with existing decision making methods to solve multi-criteria decision-making problems, as well as other engineering problems that are complex, hard to model and/or include incomplete and vague data. By providing new ideas, suggestions and directions for the solution of complex problems in engineering and decision making, it represents an excellent guide for researchers, lecturers and postgraduate students pursuing research on neutrosophic decision making, and more in general in the area of industrial and management engineering.
Neutrosophic hesitant fuzzy set is the generalization of neutrosophic set and the hesitant fuzzy set, which can easily express the uncertain, incomplete and inconsistent information in cognitive activity, and the VIKOR (from Serbian:VIseKriterijumska Optimizacija I Kompromisno Resenje) method is an effective decision making tool which can select the optimal alternative by the maximum ‘‘group utility’’ and minimum of an ‘‘individual regret’’ with cognitive computation.