Simulation optimization using particle swarm optimization algorithm with application to assembly line design
Simulation optimization using particle swarm optimization algorithm with application to assembly line design
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DOI：
10.1016/j.asoc.2009.12.020
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
R. Kuo;Changxi Yang
中科院分区：
文献类型：
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作者：
R. Kuo;Changxi Yang
装配线设计是生产系统的重要组成部分。一些流程需要进行更改以提高效率。计算机模拟在工艺设计中的应用已有几十年的历史。传统上，仿真必须运行所有可能的替代品的装配线，并没有被认为是一种优化技术。因此，本研究采用基于相似性变异的粒子群优化（PSO）算法进行模拟优化，以优化生产系统中的管理参数。通过实验设计和统计检验，仿真结果表明，该方法求解装配线设计问题的效果优于遗传算法和传统的粒子群算法。
Assembly line design is an important part of production system. Some processes need to undergo changes in order to increase in efficiency. Computer simulation has been applied on process design for many decades. Traditionally, simulation had to run all possible alternatives of assembly line and was not considered as an optimization technique. Thus, this study employs particle swarm optimization (PSO) algorithm which is with mutation based on similarity for simulation optimization in order to optimize the managerial parameters in production system. Through experimentation designs and statistics tests, the simulation results show that the proposed method is better than other algorithms, like genetic algorithm and conventional PSO algorithm for solving assembly line design problem.