Описание: This book introduces readers to the latest advances in and approaches to intuitionistic fuzzy decision-making methods. Examining a host of decision-making methods, most of which are based on intuitionistic fuzzy aggregation operators, its goal is to offer readers a new way to study decision-making methods in the intuitionistic fuzzy environment.
Описание: This book covers theory and application of such MADM methods as Analytic Hierarchy Process, Technique for Order Preference by Similarity to Ideal Solution, VIsekriterijumsko KOmpromisno Rangiranje and more. Offers novel MADM methods, and includes computer code.
Описание: This book gathers extended versions of the best papers presented at the 8th IEEE conference on Intelligent Systems, held in Sofia, Bulgaria on September 4–6, 2016, which are mainly related to theoretical research in the area of intelligent systems. The main focus is on novel developments in fuzzy and intuitionistic fuzzy sets, the mathematical modelling tool of generalized nets and the newly defined method of intercriteria analysis. The papers reflect a broad and diverse team of authors, including many young researchers from Australia, Bulgaria, China, the Czech Republic, Iran, Mexico, Poland, Portugal, Slovakia, South Korea and the UK.
Автор: Tzeng Gwo-Hshiung, Huang Jih-Jeng Название: Multiple Attribute Decision Making: Methods and Applications ISBN: 1439861579 ISBN-13(EAN): 9781439861578 Издательство: Taylor&Francis Рейтинг: Цена: 26796.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Decision makers are often faced with several conflicting alternatives. How do they evaluate trade-offs when there are more than three criteria? To help people make optimal decisions, scholars in the discipline of multiple criteria decision making (MCDM) continue to develop new methods for structuring preferences and determining the correct relative weights for criteria. A compilation of modern decision-making techniques, Multiple Attribute Decision Making: Methods and Applications focuses on the fuzzy set approach to multiple attribute decision making (MADM). Drawing on their experience, the authors bring together current methods and real-life applications of MADM techniques for decision analysis. They also propose a novel hybrid MADM model that combines DEMATEL and analytic network process (ANP) with VIKOR procedures.
The first part of the book focuses on the theory of each method and includes examples that can be calculated without a computer, providing a complete understanding of the procedures. Methods include the analytic hierarchy process (AHP), ANP, simple additive weighting method, ELECTRE, PROMETHEE, the gray relational model, fuzzy integral technique, rough sets, and the structural model. Integrating theory and practice, the second part of the book illustrates how methods can be used to solve real-world MADM problems. Applications covered in the book include:
AHP to select planning and design services for a construction project
TOPSIS and VIKOR to evaluate the best alternative-fuel vehicles for urban areas
ELECTRE to solve network design problems in urban transportation planning
PROMETEE to set priorities for the development of new energy systems, from solar thermal to hydrogen energy
Fuzzy integrals to evaluate enterprise intranet web sites
Rough sets to make decisions in insurance marketing
Helping readers understand how to apply MADM techniques to their decision making, this book is suitable for undergraduate and graduate students as well as practitioners.
Описание: This book presents 27 methods of the Multiple Attribute Decision Making (MADM), which are not discussed in the existing books, nor studied in details, using more applications. Multiple Criteria Decision Making (MCDM) is sum of the decision making techniques.
Описание: This book presents 27 methods of the Multiple Attribute Decision Making (MADM), which are not discussed in the existing books, nor studied in details, using more applications. Nowadays, decision making is one of the most important and fundamental tasks of management as an organizational goal achievement that depends on its quality. Decision making includes the correct expression of objectives, determining different and possible solutions, evaluating their feasibility, assessing the consequences, and the results of implementing each solution, and finally, selecting and implementing the solution. Multiple Criteria Decision Making (MCDM) is sum of the decision making techniques. MCDM is divided into the Multiple Objective Decision Making (MODM) for designing the best solution and MADM for selecting the best alternative. Given that the applications of MADM are mostly more than MODM, wide various techniques have been developed for MADM by researchers over the last 60 years, and the current book introduces some of the other new MADM methods.
Описание: This is the first book to provide a comprehensive and systematic introduction to the ranking methods for interval-valued intuitionistic fuzzy sets, multi-criteria decision-making methods with interval-valued intuitionistic fuzzy sets, and group decision-making methods with interval-valued intuitionistic fuzzy preference relations.
Описание: This is the first book to provide a comprehensive and systematic introduction to the ranking methods for interval-valued intuitionistic fuzzy sets, multi-criteria decision-making methods with interval-valued intuitionistic fuzzy sets, and group decision-making methods with interval-valued intuitionistic fuzzy preference relations.
Автор: Zolghadr-Asli Babak, Bozorg-Haddad Omid, Loбiciga Hugo A. Название: A Handbook on Multi-Attribute Decision-Making Methods ISBN: 1119563496 ISBN-13(EAN): 9781119563495 Издательство: Wiley Рейтинг: Цена: 16149.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Clear and effective instruction on MADM methods for students, researchers, and practitioners.
A Handbook on Multi-Attribute Decision-Making Methods describes multi-attribute decision-making (MADM) methods and provides step-by-step guidelines for applying them. The authors describe the most important MADM methods and provide an assessment of their performance in solving problems across disciplines. After offering an overview of decision-making and its fundamental concepts, this book covers 20 leading MADM methods and contains an appendix on weight assignment methods. Chapters are arranged with optimal learning in mind, so you can easily engage with the content found in each chapter. Dedicated readers may go through the entire book to gain a deep understanding of MADM methods and their theoretical foundation, and others may choose to review only specific chapters. Each standalone chapter contains a brief description of prerequisite materials, methods, and mathematical concepts needed to cover its content, so you will not face any difficulty understanding single chapters. Each chapter:
Describes, step-by-step, a specific MADM method, or in some cases a family of methods
Contains a thorough literature review for each MADM method, supported with numerous examples of the method's implementation in various fields
Provides a detailed yet concise description of each method's theoretical foundation
Maps each method's philosophical basis to its corresponding mathematical framework
Demonstrates how to implement each MADM method to real-world problems in a variety of disciplines
In MADM methods, stakeholders' objectives are expressible through a set of often conflicting criteria, making this family of decision-making approaches relevant to a wide range of situations. A Handbook on Multi-Attribute Decision-Making Methods compiles and explains the most important methodologies in a clear and systematic manner, perfect for students and professionals whose work involves operations research and decision making.
Описание: This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent combinations, and their applications in the areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization.
Описание: This book gathers extended versions of the best papers presented at the 8th IEEE conference on Intelligent Systems, held in Sofia, Bulgaria on September 4-6, 2016, which are mainly related to theoretical research in the area of intelligent systems.
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