Scheduling parallel batch processing machines with arbitrary job sizes and incompatible job families
Scheduling parallel batch processing machines with arbitrary job sizes and incompatible job families
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DOI：
10.1080/00207540410001704041
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发表时间：
2004-10
影响因子：
9.2
通讯作者：
Shie-Gheun Koh *;Pyung-Hoi Koo;Jaewon Ha;Woon-Seek Lee
中科院分区：
文献类型：
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作者：
Shie-Gheun Koh *;Pyung-Hoi Koo;Jaewon Ha;Woon-Seek Lee
受多层陶瓷电容器生产线瓶颈作业的启发，研究了并行批处理机的调度问题，其中多个作业可以作为一批在一台机器上同时加工。作业的数量彼此不同，并且每个作业属于其中所有作业具有相同处理时间的家庭。在这种情况下，我们分析了三类性能指标分别为完工时间、总完工时间和总加权完工时间的问题。由于这些问题都是NP难的，我们提出了一些启发式算法，并设计了遗传算法来解决这些问题。通过一些计算实验，我们评估了所提出的启发式算法的性能，包括针对这三个问题的遗传算法。
Motivated by a bottleneck operation in an MLCC (multi-layer ceramic capacitor) production line, we study the scheduling problem of parallel batch processing machines in which a number of jobs can be processed simultaneously in a machine as a batch. Volumes of the jobs are different from each other and each job belongs to the family in which all jobs have the same processing time. In this situation, we analyse three kinds of problems whose performance measures are makespan, total completion time, and total weighted completion time, respectively. Since these problems are known to be NP-hard, we propose a number of heuristics and design genetic algorithms for the problems. Through some computational experiments, we evaluate the performances of the heuristic algorithms proposed, including the genetic algorithms for each of three problems.