Fuzzy Particle Swarm Optimization Algorithm for a Supplier Clustering Problem

Journal of Optimization in Industrial Engineering

مقاله 3، Volume 1، Issue 1، مرداد 2008، صفحه 17-24   

نویسندگان

esmaeil Mehdizadeh¹؛ reza Tavakkoli Moghaddam²

¹Islamic Azad University, Science and Research Branch Branch

²Department of Industrial Engineering, Faculty of Engineering, University of Tehran

چکیده

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 using particle swarm optimization (PSO) algorithm for clustering suppliers under fuzzy environments and classifying smaller groups with similar characteristics.

Our numerical analysis indicates that the proposed PSO improves the performance of the fuzzy c-means (FCM) algorithm.

کلیدواژه‌ها

fuzzy clustering؛ supplier clustering problem and particle swarm optimization