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

机译:Flow Shop调度系统中的抢占式即时调度问题

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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.
机译:流水车间调度问题在制造业中得到了广泛的应用,在学术领域引起了广泛的关注。从另一方面讲,按时交付产品和服务是当今公司的主要需求;提早交货和延误交货时间将导致额外的成本,例如持有或罚款成本。在本文中,考虑了具有抢占和机器空闲时间假设的实时(JIT)流水车间调度问题,其中目标函数使加权早期和延误的总和最小。针对该问题制定了新的非线性数学模型,并且由于问题的复杂性,已采用元启发式方法来解决该问题,以找到最佳解。算法的参数由田口方法设定。每个参数分三个级别进行测试。通过实施许多大小不同的问题,可以确定这些级别。所提出的模型通过三种元启发式算法进行求解:遗传算法(GA),帝国主义竞争算法(ICA)以及GA和ICA的混合。为了评估所提出算法的性能,已经设计了许多测试问题。计算结果表明,在合理的计算时间内找到最佳解决方案的过程中,混合方法的性能优于GA和ICA。

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