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Simulation-based optimization for solving a hybrid flow shop scheduling problem

机译:基于仿真的优化解决混合流水车间调度问题

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This paper describes the solution of a hybrid flow shop (HFS) scheduling problem of a printed circuit board assembly. The production comprises four surface-mount device placement machines on the first stage and five automated optical inspection machines on the second stage. The objective is to minimize the makespan and the total tardiness. The paper compares three approaches to solve the HFS scheduling problem: an integrated simulation-based optimization algorithm (ISBO) developed by the authors and two metaheuristics, simulated annealing and tabu search. All approaches lead to an improvement in terms of producing more jobs on time while minimizing the makespan compared to the decision rules used so far in the analyzed company. The ISBO delivers results much faster than the two metaheuristics. The two metaheuristics lead to slightly better results than the ISBO in terms of total tardiness.
机译:本文介绍了印刷电路板组件的混合流水车间(HFS)调度问题的解决方案。该产品在第一阶段包括四台表面贴装设备放置机,在第二阶段包括五台自动光学检测机。目的是使制造期和总拖延最小。本文比较了解决HFS调度问题的三种方法:作者开发的集成的基于仿真的优化算法(ISBO)和两种元启发式方法,即模拟退火和禁忌搜索。与目前在分析公司中使用的决策规则相比,所有方法都可以在按时生产更多工作的同时,最大程度地缩短工期,从而带来改进。 ISBO提供结果的速度比两种元启发式方法要快得多。就总拖延率而言,这两种元启发法比ISBO产生的结果略好。

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