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首页> 外文期刊>International Journal of Production Research >Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness
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Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness

机译：具有单个到期日的工作的单元加载和家庭计划，以最大程度地减少延迟

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This paper focuses on cell loading and family scheduling in a cellular manufacturing environment. The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the presence of individual due dates for every job in a family and also allowing family splitting among cells. Three methods are examined in order to solve this problem, namely mathematical modelling, genetic algorithms (GA) and heuristics. The results showed that GA is capable of finding the optimal solution with varying frequency of 60-100% and it is efficient as compared to the mathematical modelling especially for larger problems in terms of execution times. The heuristics, on the other hand, were easy to implement but they could not find the optimal solution. The results of experimentation also showed that family splitting was observed in all multi-cell optimal solutions and therefore it can be concluded that family splitting is a good strategy for the problem considered in this paper.
机译：本文重点介绍蜂窝制造环境中的单元加载和族调度。绩效衡量标准是最大程度地减少工作的拖延时间。这项研究与其他研究区分开来的是，一个家庭中每个工作的个人到期日的存在，还允许家庭在各个单元之间分裂。为了解决这个问题，研究了三种方法，即数学建模，遗传算法（GA）和启发式方法。结果表明，GA能够以60-100％的变化频率找到最佳解决方案，并且与数学模型相比，它特别有效，特别是对于执行时间较大的问题。另一方面，启发式方法易于实现，但找不到最佳解决方案。实验结果还表明，在所有多单元最优解决方案中均观察到家庭分裂，因此可以得出结论，家庭分裂是解决本文所考虑问题的一种很好的策略。

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