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首页> 外文期刊>International Journal of Services and Operations Management >Group scheduling in a cellular manufacturing shop to minimise total tardiness and nT: a comparative genetic algorithm and mathematical modelling approach
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Group scheduling in a cellular manufacturing shop to minimise total tardiness and nT: a comparative genetic algorithm and mathematical modelling approach

机译:在蜂窝制造车间进行组调度以最大程度地减少总拖延和nT:一种比较遗传算法和数学建模方法

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摘要

In this paper, family and job scheduling in a cellular manufacturing shop is addressed where jobs have individual due dates. The objectives are to minimise total tardiness and the number of tardy jobs. Family splitting among cells is allowed but job splitting is not. Two optimisation methods are employed in order to solve this problem, namely mathematical modelling (MM) and genetic algorithm (GA). The results showed that GA found the optimal solution for most of the problems with high frequency. Furthermore, the proposed GA is efficient compared to the MM especially for larger problems in terms of execution times. Other critical aspects of the problem such as family preemption only, impact of family splitting on common due date scenarios and dual objective scenarios are also solved. In short, the proposed comparative approach provides critical insights for the group scheduling problem in a cellular manufacturing shop with distinctive cases.
机译:在本文中,解决了蜂窝式制造工厂中的家庭和工作计划,其中工作有各自的到期日。目标是最大程度地减少总拖延和拖延的工作数量。允许在牢房中进行家庭分裂,但不允许进行工作分裂。为了解决该问题,采用了两种优化方法,即数学建模(MM)和遗传算法(GA)。结果表明,遗传算法为大多数高频问题找到了最佳解决方案。此外,与MM相比,拟议的GA是高效的,特别是对于执行时间较大的问题。还解决了该问题的其他关键方面,例如仅家庭优先权,家庭分裂对共同到期日方案和双重目标方案的影响。简而言之,所提出的比较方法为具有特殊情况的蜂窝制造车间中的组调度问题提供了重要的见识。

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