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The single machine scheduling problem with sequence-dependent setup times and a learning effect on processing times

机译:单个机器调度问题与序列相关的设置次数和关于处理时间的学习效果

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For the past few years, learning effect has been receiving wide attention in the scheduling problems. There are many studies that take into account the learning effect with several structural constraints and some specific conditions of machine scheduling problems. However, very few studies have explored the scheduling problem including learning effect and sequence-dependent setup times simultaneously, although both are found in the scheduling literature. Therefore, this study addresses an NP-Hard problem of minimizing the total tardiness on a single machine with sequence-dependent setup times and a position-based learning effect on processing times. Several dominance properties are verified and a lower bound is provided to develop a branch and bound algorithm for solving the problem. In addition, four heuristic algorithms (two genetic algorithms and two variable neighborhood search algorithms) are developed in order to obtain near optimal solutions in reasonable time limits. Furthermore, some computational experiments are performed on randomly generated test problems to evaluate the performance of the algorithms. (C) 2018 Elsevier B.V. All rights reserved.
机译:在过去几年中,学习效果在调度问题中得到了广泛的关注。有许多研究考虑了几种结构约束和一些机器调度问题的具体条件的学习效果。然而,很少有研究探索了调度问题,包括同时包括学习效果和序列相关的设置时间,尽管两者都在调度文献中找到。因此,本研究解决了利用序列依赖的设置时间和基于位置的学习效果最小化单个机器上的总迟到的NP难题问题。验证了几个优势特性,并提供了下限以开发用于解决问题的分支和绑定算法。另外,开发了四种启发式算法(两个遗传算法和两个可变邻域搜索算法),以便在合理的时间限制中获得附近的最佳解决方案。此外,对随机生成的测试问题进行了一些计算实验以评估算法的性能。 (c)2018 Elsevier B.v.保留所有权利。

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