The Preemptive Just-in-time Scheduling Problem in a Flow Shop Scheduling System

Q2 Engineering
J. Rezaeian, Sadegh Hosseini-Kia, I. Mahdavi
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引用次数: 0

Abstract

Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs.  In this paper, just-in-time (JIT) flow shop scheduling problem with preemption and machine idle time assumptions is considered in which objective function is minimizing the sum of weighted earliness and tardiness. A new non-linear mathematical model is formulated for this problem and due to high complexity of the problem meta-heuristic approaches have been applied to solve the problem for finding optimal solution. The parameters of algorithms are set by Taguchi method. Each parameter is tested in three levels. By implementation of many problems with different sizes these levels are determined .The proposed model is solved by three meta-heuristic algorithms: genetic algorithm (GA), imperialist competitive algorithm (ICA) and hybrid of GA and ICA. To evaluate the performance of the proposed algorithms many test problems have been designed. The Computational results indicate the superiority of the performance of hybrid approach than GA and ICA in finding thebest solution in reasonable computational time.
流车间调度系统中的抢占式准时调度问题
流水车间调度问题在制造业中有着广泛的应用,引起了学术界的广泛关注。从另一个角度来看,按时交付产品和服务是当今公司的主要需求;提前和延迟交货时间将导致额外的成本,如持有或罚款成本。本文研究了具有抢占和机器空闲时间假设的JIT (just-in-time)流车间调度问题,其目标函数是最小化加权早、迟的总和。针对该问题建立了一个新的非线性数学模型,并由于问题的高度复杂性,采用元启发式方法求解该问题以寻找最优解。算法参数采用田口法确定。每个参数分为三个级别进行测试。该模型采用三种元启发式算法求解:遗传算法(GA)、帝国主义竞争算法(ICA)以及遗传算法和帝国主义竞争算法的混合算法。为了评估所提出算法的性能,设计了许多测试问题。计算结果表明,混合方法在合理的计算时间内找到最优解的性能优于遗传算法和ICA。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Optimization in Industrial Engineering
Journal of Optimization in Industrial Engineering Engineering-Industrial and Manufacturing Engineering
CiteScore
2.90
自引率
0.00%
发文量
0
审稿时长
32 weeks
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