Addressing the weaknesses of multi-criteria decision-making methods using Python

Abstract

The book aims to draw attention to the weaknesses in Multi-Criteria Decision-Making (MCDM) methods and provide insights to improve the decision-making process. By addressing these weaknesses, it seeks to enhance the accuracy and effectiveness of MCDM methods in selecting the best alternatives in various fields. The book covers popular MCDM methods such as TOPSIS, ELECTRE, VIKOR, and PROMETHEE. It compares traditional methods with the proposed modified Human Development Index (HDI) data using Python code examples. The target audience for the book includes computer scientists, engineers, business, and financial management professionals, as well as anyone interested in MCDM and its applications. © 2024 Elsevier B.V., All rights reserved.