Fuzzy TOPSIS

Logic, Approaches, and Case Studies
1. Auflage 2024
ISBN: 978-0-367-76749-5
Verlag: Taylor & Francis Ltd (Sales)

Buch, Englisch, 216 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 313 g

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.

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

El Alaoui, Mohamed

Fachgebiete

• Geisteswissenschaften Design Produktdesign, Industriedesign
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Produktionsmanagement, Qualitätskontrolle
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Informationstheorie, Kodierungstheorie
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Mathematik | Informatik Mathematik Stochastik Bayesianische Inferenz
• Technische Wissenschaften Technik Allgemein Industrial Engineering
• Mathematik | Informatik Mathematik Operations Research
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie

Inhaltsverzeichnis

1. Uncertainty. 2. Non-Classical Logics. 3. Fuzzy Logic. 4. Frequently Used Methods. 5. TOPSIS Methodology and Limits. 6. Fuzzy TOPSIS. 7. Intuitionistic Fuzzy TOPSIS. 8. Other Fuzzy TOPSIS Approaches.

Über Autor(innen)

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.