This edition first published 2020
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The present book provides a comprehensive and prudently founded fuzzy‐set‐based framework for a challenging and extremely important area of decision‐making. It reflects ways of representing and handling diverse manifestations of the uncertainty factor and the multicriteria nature of problems arising in system design, planning, operation, and control. The models and methods for multiobjective and multiattribute decision‐making are presented along with their applications to a wide range of real‐world problems coming from different areas. The book comes with a wealth of detailed appealing examples and carefully selected real‐world case studies. As such, it stresses the hands‐on nature of the exposition of the overall material.
Owing to the coverage of the material, we hope that this book will appeal to the communities active in various areas, in which decision‐making becomes of paramount relevance: operations research, systems analysis, engineering, management, economics, and administration. Given the way in which the material is structured, the book can also serve as a useful reference material for graduate and senior undergraduate students on courses related to the areas indicated here, as well as courses on decision‐making, risk management, numerical methods, and knowledge‐based systems. The book could be also of interest to system analysts and researchers in areas where decision‐making technologies are of paramount relevance.
The book covers the following fundamental topics spread across seven chapters:
The present book arises as a natural development and extension of the book Fuzzy Multicriteria Decision‐Making: Models, Methods, and Application (co‐authored by W. Pedrycz, P. Ekel, and R. Parreiras), published by John Wiley & Sons in 2011. It augments and deepens many of the topics covered in the previous book. Also, this book includes completely new, far reaching, and original results. For instance, we cover an approach involving the consideration of choice criteria of the classical approach to dealing with uncertainty of information as objective functions in multiobjective decision‐making under uncertainty. The use of this approach helps the decision maker to overcome contradictions appearing in the analysis of multiobjective problems under conditions of uncertainty on the basis of aggregating payoff matrices.
In addition, currently, we encounter more and more problems whose essence requires the consideration of the objectives (for instance, investment attractiveness, political effect, maintenance flexibility, etc.) formed with the use of qualitative information (based on the knowledge, experience, and intuition of involved experts) at all stages of the ongoing decision process. Taking this into account, the results of the book are aimed at generating multiobjective solutions within the framework of the possibilistic approach, including multicriteria robust solutions, by constructing representative combinations of initial data, states of nature, or scenarios with direct usage of qualitative information presented along with quantitative information. It permits one to realize a process of information fusion within the multiobjective models. The described results provide the possibility for experts to apply diverse preference formats processed by transformation functions.
We would like express thanks our colleagues and friends: R.C. Berredo, A.F. Bondarenko, E.A. Galperin, A.C. Lisboa, R.M. Palhares, R.O. Parreiras, A.V. Prakhovnik (in memoriam), J.C.B. Queiroz, G.L. Soares, R. Schinzinger (in memoriam), D.A.G. Vieira, and V.V. Zorin for thorough discussions, encouragement, and support.
We would like to thank our graduate students: T.M.M. Coelho, L.R. Figueiredo, M.F.D. Junges, R.B. Pereira, V.F.D. Ramalho (the results of his M.Sc. dissertation have been helpful in writing Chapter 7 of the book), S.P. Rocha, J.N. Silva, L.M.L. Silva, and V. Tkachenko for their dedication and hard work.
We are also grateful to the team of professionals at Wiley, including Brett Kurzman, Victoria Bradshaw, Karthiga Mani, and Lynette Woodward, for providing expert advice and encouragement, and assistance during the tenure of the project.