Solving Fuzzy Multiple Objective Dynamic Cellular Manufacturing System Problem using a Hybrid Algorithm of NSGA-II and Progressive Simulated Annealing

Abstract

Cellular manufacturing systems (CMSs) are as one of the most important manufacturing methods.In this paper, is presented a multiple objective model to constitute a CMS under dynamic conditions subject to flexibility of operation processing, assigning machine to each operation and defining cost parameters as fuzzy numbers. In the proposed model, are considered objectives such as minimization of manufacturing system costs and fuzzy costs variance. Also in this paper, in order to attainment of effective solutions, is proposed a hybrid algorithm by NSGA-II and progressive Simulated Annealing (SA) and is applied experimental design of Taguchi for tuning the parameters of this algorithm. For surveying efficiency of the proposed algorithm, results obtained from solving several different sample problems, based on criteria of CPU time, generational distance, spacing and quality metric, are compared and analyzed with results of NSGA-II original algorithm.

Keywords

• cellular manufacturing system scheduling
• fuzzy theory
• nsga-ii algorithm, progressive simulated annealing (sa)