Using Fuzzy Logic to Make Decisions Based on Multiple Criteria

Abstract

Multi-Criteria Decision-Making (MCDM) is a process used to evaluate and select the best alternative from a set of options, considering multiple conflicting criteria. In many real-world applications, decision-making involves uncertainty, imprecision, and vagueness, which traditional decision-making methods, such as the Analytical Hierarchy Process (AHP) and TOPSIS, often need help. Fuzzy logic, a mathematical framework that models uncertainty by allowing partial membership in sets, provides an effective solution to these challenges. Fuzzy logic enhances MCDM by enabling decision-makers to handle imprecise information and subjective judgments. This paper investigates the application of fuzzy logic in MCDM and provides a comprehensive review of various fuzzy-based techniques, including fuzzy AHP, fuzzy TOPSIS, fuzzy VIKOR, and fuzzy ELECTRE. Each method is explored to demonstrate how fuzzy logic has been integrated to improve the decision-making process.

Furthermore, the paper discusses the integration of fuzzy logic with other computational intelligence methods, such as machine learning algorithms and optimization techniques, to address complex MCDM problems more effectively. The paper also highlights the advancements in fuzzy MCDM, discusses its challenges, and identifies future research directions. The goal is to present an overview of fuzzy logic's potential to enhance decision-making processes in diverse fields such as healthcare, finance, energy management, and engineering