A new particle swarm algorithm for a multi-objective mixed-model assembly line sequencing problem

作     者：Rahimi-Vahed, A. R. Mirghorbani, S. M. Rabbani, M. 

作者机构：Univ Tehran Fac Engn Dept Ind Engn Tehran Iran 

出 版 物：《SOFT COMPUTING》 (Soft Comput.)

年 卷 期：2007年第11卷第10期

页      面：997-1012页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：mixed-model assembly line multi-objective sequencing problem just-in-time multi-objective particle swarm multi-objective genetic algorithm 

摘      要：The sequencing of products for mixed-model assembly line in Just-in-Time manufacturing systems is sometimes based on multiple criteria. In this paper, three major goals are to be simultaneously minimized: total utility work, total production rate variation, and total setup cost. A multi-objective sequencing problem and its mathematical formulation are described. Due to the NP-hardness of the problem, a new multi-objective particle swarm (MOPS) is designed to search locally Pareto-optimal frontier for the problem. To validate the performance of the proposed algorithm, various test problems are solved and the reliability of the proposed algorithm, based on some comparison metrics, is compared with three distinguished multi-objective genetic algorithms (MOGAs), i.e. PS-NC GA, NSGA-II, and SPEA-II. Comparison shows that MOPS provides superior results to MOGAs.