APPLICATION OF FUZZY ANALYSIS IN OPTIMIZATION AND DECISION MAKING

Abstract

Fuzzy analysis, based on Lotfi A. Zadeh’s fuzzy set theory, is an effective tool for addressing
problems involving uncertainty in optimization and decision making. In optimization, it enables the
modeling of ambiguous parameters such as costs, demand, or resources, facilitating flexible solutions
in fields like supply chain management and production. In decision making, fuzzy analysis supports
the evaluation of options based on unclear criteria, with applications in finance, medicine, and risk
management. This paper presents the theoretical foundation, practical applications, and a specific
example of optimizing transportation costs in a supply chain, where demand and costs are represented as
fuzzy sets. The example results show an optimal solution with an average cost of 545 USD, ranging from
430 to 650 USD, outperforming traditional methods due to its ability to handle uncertainty.