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首页> 外文期刊>Computers & Industrial Engineering >A column generation heuristic for complex job shop multiple orders per job scheduling
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A column generation heuristic for complex job shop multiple orders per job scheduling

机译:列生成启发式,用于每个作业调度的复杂作业车间多个订单

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摘要

Scheduling in semiconductor manufacturing is a challenging task due to inherent complexities like assignment of multiple customer orders to front opening unified pods (FOUPs), batch processing in multiple toolgroups with parallel machines, and re-entrant flow. A disjunctive-network-flow mixed integer program (DNF) and a column generation heuristic are presented to minimize the sum of weighted customer order completion times in a complex job shop environment. In addition, a lower bound estimation approach for the complex job shop problem is presented. The column generation heuristic obtains solutions that are very close to that of the time constrained DNF formulation for problem instances with zero order ready times. However, column generation's performance differs considerably for problem instances with non-zero order ready times and is able to solve large problem instances in a matter of minutes.
机译:由于固有的复杂性,例如将多个客户订单分配给前端开放式统一吊舱(FOUP),使用并行机在多个工具组中进行批处理以及重入流程,半导体制造中的调度工作是一项艰巨的任务。提出了分离网络流混合整数程序(DNF)和列生成启发式算法,以最大程度地减少复杂作业车间环境中加权的客户订单完成时间的总和。另外,提出了一种针对复杂作业车间问题的下界估计方法。对于零阶准备时间的问题实例,列生成启发式方法获得的解决方案与时间约束DNF公式非常接近。但是,对于具有非零阶准备时间的问题实例,列生成的性能差异很大,并且能够在几分钟内解决大型问题实例。

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