Encyclopedia of Multi-Attribute Decision Making (MADM)

Gholamreza Haseli, Muhammet Deveci, Mostafa Hajiaghaei-Keshteli

• Publisher: Morgan Kaufmann
• Year: 2026
• Topic: Computer Science
• eBook ISBN:
  9780443332760
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

Encyclopedia of Multi-Attribute Decision Making (MADM) presents current methods in MADM in a simple way, including Sections on Weighting Methods, Extensions for the MADM Methods, Ranking Methods, and Outranking Methods. Each method chapter presents two numerical examples for each method, one simple example with less than six criteria and six alternatives, and one complex example with six or more criteria and six or more alternatives. In addition, most chapters are written by the original developers of the method, ensuring insight into and practical application of MADM. The book is also filled with over 200 full-color figures that illustrate methods and applications.The book, in one volume, demystifies the complex world of MADM, blending theoretical concepts with hands-on practices and case studies. It bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of MADM. - Includes chapters on all the current Multi-Attribute Decision Making methods, including Sections on Weighting Methods, Extensions for the MADM Methods, Ranking Methods, and Outranking Methods - Presents a consistent structure, enabling easier learning of methods - Provides two numerical examples for each method, one simple example with less than six criteria and six alternatives, and one complex example with six or more criteria and six or more alternatives - Includes comprehensive coverage of balanced theory and practice, thus ensuring a strong theoretical foundation paired with actionable insights for real-world applications

Table of contents

• Title of Book
• Section 1: Weighting methods
• Section 2: Extensions for the MADM methods
• Section 3: Ranking methods
• Section 4: Outranking methods
• Index