A hybrid fuzzy clustering PSO algorithm for a clustering supplier problem

This paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. During recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions is usually complex and unstructured. In general, many quantitative and qualitative factors, such as quality, price, and flexibility and delivery performance, must be considered to determine suitable suppliers. The aim of this study is to present a new approach for a particle swarm optimization (PSO) algorithm to clustering suppliers under fuzzy environments into manageable smaller groups with similar characteristics. Our numerical analysis indicates that the proposed PSO improves the performance of the fuzzy c-means (FCM) algorithm.