文章基本信息

标题：Multi-objective optimization algorithms for mixed model assembly line balancing problem with parallel workstations
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作者：Masoud Rabbani ; Reyhaneh Siadatian ; Hamed Farrokhi-Asl 等
期刊名称：Cogent Engineering
电子版ISSN：2331-1916
出版年度：2016
卷号：3
期号：1
页码：1158903
DOI：10.1080/23311916.2016.1158903
语种：English
出版社：Taylor and Francis Ltd
摘要：Abstract This paper deals with mixed model assembly line (MMAL) balancing problem of type-I. In MMALs several products are made on an assembly line while the similarity of these products is so high. As a result, it is possible to assemble several types of products simultaneously without any additional setup times. The problem has some particular features such as parallel workstations and precedence constraints in dynamic periods in which each period also effects on its next period. The research intends to reduce the number of workstations and maximize the workload smoothness between workstations. Dynamic periods are used to determine all variables in different periods to achieve efficient solutions. A non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) are used to solve the problem. The proposed model is validated with GAMS software for small size problem and the performance of the foregoing algorithms is compared with each other based on some comparison metrics. The NSGA-II outperforms MOPSO with respect to some comparison metrics used in this paper, but in other metrics MOPSO is better than NSGA-II. Finally, conclusion and future research is provided.
关键词：multi-objective optimization ; mixed model assembly lines ; balancing ; sequencing ; parallel workstations