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A two-stage heuristic for single machine capacitated lot-sizing and scheduling with sequence-dependent setup costs

机译:两阶段启发式,用于单台机器,可按批量确定批量和计划,并具有与序列相关的设置成本

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摘要

This paper considers a single machine capacitated lot-sizing and scheduling problem. The problem is to determine the lot sizes and the sequence of lots while satisfying the demand requirements and the machine capacity in each period of a planning horizon. In particular, we consider sequence-dependent setup costs that depend on the type of the lot just completed and on the lot to be processed. The setup state preservation, i.e., the setup state at the end of a period is carried over to the next period, is also considered. The objective is to minimize the sum of setup and inventory holding costs over the planning horizon. Due to the complexity of the problem, we suggest a two-stage heuristic in which an initial solution is obtained and then it is improved using a backward and forward improvement method that incorporates various priority rules to select the items to be moved. Computational tests were done on randomly generated test instances and the results show that the two-stage heuristic outperforms the best existing algorithm significantly. Also, the heuristics with better priority rule combinations were used to solve case instances and much improvement is reported over the conventional method as well as the best existing algorithm.
机译:本文考虑单机容量大的批量和调度问题。问题是确定批次的大小和批次的顺序,同时满足计划范围内每个时期的需求和机器容量。特别是,我们考虑与序列相关的设置成本,该成本取决于刚完成的批次的类型和要处理的批次。还考虑建立状态保存,即,在一个周期结束时的建立状态被转移到下一个周期。目的是在计划范围内将设置和库存持有成本的总和最小化。由于问题的复杂性,我们建议采用两阶段启发式方法,在该方法中,先获取初始解,然后使用向后和向前的改进方法对其进行改进,该方法结合了各种优先级规则来选择要移动的项目。对随机生成的测试实例进行了计算测试,结果表明,两阶段启发式算法明显优于现有的最佳算法。同样,具有更好优先级规则组合的启发式算法被用来解决案例,并且与传统方法以及现有的最佳算法相比,有了很大的改进。

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