Applications of Fuzzy Optimization and Fuzzy Decision Making
Applications of Fuzzy Optimization and Fuzzy Decision Making

Author: Vassilis C Gerogiannis

Publisher:

Published: 2021-10-26

Total Pages: 416

ISBN-13: 9783036522654

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The aim of the Special Issue "Applications of Fuzzy Optimization and Fuzzy Decision Making" is to expand the applicability of fuzzy optimization and decision making for solving various types of problems in the areas of economics, business, engineering, management, operations research, etc. Any experimental research or empirical study of theoretical developments in fuzzy optimization and decision making is highly welcome. Additionally, research papers presenting solution methods and/or studying their computational complexity, and proposing new algorithms to solve fuzzy optimization and decision making problems, in an effective and efficient manner, are also welcome. We are looking forward to receive innovative approaches that apply, in practical settings, state-of-the art mathematical/algorithmic techniques from fuzzy technology, computational intelligence and soft-computing methodologies, with the aim to offer robust solutions for complex optimization and decision making problems characterized by non-probabilistic uncertainty, vagueness, ambiguity, and hesitation. Such type of papers will address the suitability, validity, and advantages of using fuzzy technologies and the enhancement of them using intelligent methods to treat real-life problems from various disciplines.

Multi-objective Group Decision Making
Multi-objective Group Decision Making

Author: Jie Lu

Publisher: Imperial College Press

Published: 2007

Total Pages: 407

ISBN-13: 1860948596

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This book proposes a set of models to describe fuzzy multi-objective decision making (MODM), fuzzy multi-criteria decision making (MCDM), fuzzy group decision making (GDM) and fuzzy multi-objective group decision-making problems, respectively. It also gives a set of related methods (including algorithms) to solve these problems. One distinguishing feature of this book is that it provides two decision support systems software for readers to apply these proposed methods. A set of real-world applications and some new directions in this area are then described to further instruct readers how to use these methods and software in their practice.

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making
Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making

Author: Cengiz Kahraman

Publisher: Springer

Published: 2019-07-05

Total Pages: 1386

ISBN-13: 3030237567

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This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.

Type-2 Fuzzy Decision-Making Theories, Methodologies and Applications
Type-2 Fuzzy Decision-Making Theories, Methodologies and Applications

Author: Jindong Qin

Publisher: Springer

Published: 2019-08-22

Total Pages: 0

ISBN-13: 9789811398902

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This book integrates the type-2 fuzzy sets and multiple criteria decision making analysis in recent years and offers an authoritative treatise on the essential topics, both at the theoretical and applied end. In this book, some basic theory, type-2 fuzzy sets, methodology, algorithms, are introduced and then some compelling case studies in decision problems are covered in depth. The authors offer an authoritative treatise on the essential topics, both at the theoretical and applied end; In a systematic and logically organized way, the book exposes the reader to the essentials of the theory of type-2 fuzzy sets, methodology, algorithms, and their applications. Numerous techniques of decision making are carefully generalized by bringing the ideas of type-2 fuzzy sets; this concerns well-known methods including TOPSIS, Analytical Network Process, TODIM, and VIKOR. This book exposes the readers to the essentials of the theory of type-2 fuzzy sets, methodology, algorithms, and their applications.

Fuzzy Techniques for Decision Making 2018
Fuzzy Techniques for Decision Making 2018

Author: José Carlos R. Alcantud

Publisher: MDPI

Published: 2020-12-02

Total Pages: 776

ISBN-13: 3039364154

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Zadeh's fuzzy set theory incorporates the impreciseness of data and evaluations, by imputting the degrees by which each object belongs to a set. Its success fostered theories that codify the subjectivity, uncertainty, imprecision, or roughness of the evaluations. Their rationale is to produce new flexible methodologies in order to model a variety of concrete decision problems more realistically. This Special Issue garners contributions addressing novel tools, techniques and methodologies for decision making (inclusive of both individual and group, single- or multi-criteria decision making) in the context of these theories. It contains 38 research articles that contribute to a variety of setups that combine fuzziness, hesitancy, roughness, covering sets, and linguistic approaches. Their ranges vary from fundamental or technical to applied approaches.

Fuzzy Multicriteria Decision-Making
Fuzzy Multicriteria Decision-Making

Author: Witold Pedrycz

Publisher: John Wiley & Sons

Published: 2011-06-15

Total Pages: 328

ISBN-13: 1119957389

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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.

Fuzzy Multi-Criteria Decision Making
Fuzzy Multi-Criteria Decision Making

Author: Cengiz Kahraman

Publisher: Springer Science & Business Media

Published: 2008-08-09

Total Pages: 591

ISBN-13: 0387768130

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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.

Fuzzy Sets, Decision Making, and Expert Systems
Fuzzy Sets, Decision Making, and Expert Systems

Author: Hans-Jürgen Zimmermann

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 342

ISBN-13: 9400932499

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In the two decades since its inception by L. Zadeh, the theory of fuzzy sets has matured into a wide-ranging collection of concepts, models, and tech niques for dealing with complex phenomena which do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. Nevertheless, a question which is frequently raised by the skeptics is: Are there, in fact, any significant problem areas in which the use of the theory of fuzzy sets leads to results which could not be obtained by classical methods? The approximately 5000 publications in this area, which are scattered over many areas such as artificial intelligence, computer science, control engineering, decision making, logic, operations research, pattern recognition, robotics and others, provide an affirmative answer to this question. In spite of the large number of publications, good and comprehensive textbooks which could facilitate the access of newcomers to this area and support teaching were missing until recently. To help to close this gap and to provide a textbook for courses in fuzzy set theory which can also be used as an introduction to this field, the first volume ofthis book was published in 1985 [Zimmermann 1985 b]. This volume tried to cover fuzzy set theory and its applications as extensively as possible. Applications could, therefore, only be described to a limited extent and not very detailed.

Fuzzy Sets in Decision Analysis, Operations Research and Statistics
Fuzzy Sets in Decision Analysis, Operations Research and Statistics

Author: Roman Slowiński

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 467

ISBN-13: 1461556457

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Fuzzy Sets in Decision Analysis, Operations Research and Statistics includes chapters on fuzzy preference modeling, multiple criteria analysis, ranking and sorting methods, group decision-making and fuzzy game theory. It also presents optimization techniques such as fuzzy linear and non-linear programming, applications to graph problems and fuzzy combinatorial methods such as fuzzy dynamic programming. In addition, the book also accounts for advances in fuzzy data analysis, fuzzy statistics, and applications to reliability analysis. These topics are covered within four parts: Decision Making, Mathematical Programming, Statistics and Data Analysis, and Reliability, Maintenance and Replacement. The scope and content of the book has resulted from multiple interactions between the editor of the volume, the series editors, the series advisory board, and experts in each chapter area. Each chapter was written by a well-known researcher on the topic and reviewed by other experts in the area. These expert reviewers sometimes became co-authors because of the extent of their contribution to the chapter. As a result, twenty-five authors from twelve countries and four continents were involved in the creation of the 13 chapters, which enhances the international character of the project and gives an idea of how carefully the Handbook has been developed.

Policy Decision Modeling with Fuzzy Logic
Policy Decision Modeling with Fuzzy Logic

Author: Ali Guidara

Publisher: Springer Nature

Published: 2020-12-18

Total Pages: 140

ISBN-13: 3030626288

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This book introduces the concept of policy decision emergence and its dynamics at the sub systemic level of the decision process. This level constitutes the breeding ground of the emergence of policy decisions but remains unexplored due to the absence of adequate tools. It is a nonlinear complex system made of several entities that interact dynamically. The behavior of such a system cannot be understood with linear and deterministic methods. The book presents an innovative multidisciplinary approach that results in the development of a Policy Decision Emergence Simulation Model (PODESIM). This computational model is a multi-level fuzzy inference system that allows the identification of the decision emergence levers. This development represents a major advancement in the field of public policy decision studies. It paves the way for decision emergence modeling and simulation by bridging complex systems theory, multiple streams theory, and fuzzy logic theory.