mathematics > probability & statistics / bayesian analysis
Fuzzy Topsis: Logic, Approaches, and Case Studies
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This book aims to justify the use of fuzzy logic as a logic and as an uncertainty theory in the decision-making context. It also discusses the development of the TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) with related examples and MATLAB codes. This is the first book devoted to TOPSIS and its fuzzy versions.
It presents the use of fuzzy logic as a logic and as an uncertainty theory in the decision-making content and discusses the development of the TOPSIS method in classical and fuzzy context. The book justifies the use of fuzzy logic as an uncertainty theory and provides illustrative examples for each fuzzy TOPSIS extension, along with related MATLAB codes and case studies.
This book is for industrial engineers, operations research engineers, systems engineers, and production engineers working in the areas of decision analysis, multi-criteria decision making, and multiple objective optimization.
Mohamed EL ALAOUI holds a PhD in industrial engineering from ENSAM Meknes, Morocco and an engineering degree in industrial and production engineering from the same institution. His PhD thesis entitled "Fuzzy logic and optimization with applications in industrial and production engineering" treated several applications including: biodiesel, aggregation, consensus, similarity, goal programming, transportation, partitioning... In his academic career, he has taught various courses related to industrial engineering (projects management, quality management ...) and mechanics (solid mechanics, hydraulics ...). He also worked as a corporate trainer. He is a reviewer for few leading journals.
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