

FOLLOWUS
College of Mechanical and Electrical Engineering, Jiaxing University, Jiaxing 314000, China
Environmental and Ecological Engineering, Purdue University, West Lafayette, IN 47907, USA
School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA
Hai-yan WANG, E-mail: wanghy@mail.zjxu.edu.cn
Received:09 July 2017,
Revised:2019-;7-;3,
Published:2019-07
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Hai-yan WANG, Fu ZHAO, Hui-min GAO, et al. A three-stage method with efficient calculation for lot streaming flow-shop scheduling[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(7): 1002-1020.
Hai-yan WANG, Fu ZHAO, Hui-min GAO, et al. A three-stage method with efficient calculation for lot streaming flow-shop scheduling[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(7): 1002-1020. DOI: 10.1631/FITEE.1700457.
在工件含批量生产任务情况下如何进行最佳生产调度是一个重要的生产计划问题。通常将批量工件划分为子批处理(称为分批优化)。若子批数较大,则会大大增加工件完成时间的计算复杂性。现有研究未能考虑此类计算时间问题。本文考虑可变子批、准备时间以及子批批量约束(传输子批批量受传输设备容量限制),提出一种求解
n
个工件、
m
台机器流水车间分批优化调度方法。所提方法包含3个阶段:初始批量划分、基于生产周期/总流程时间指标快速评价法的工件排序优化、分批传输方案调整。为验证3阶段优化方法的有效性,采用5个标准数据集进行测试。实验结果表明,所提方法能节省大量计算时间,尤其对大规模问题能提供更优解。
An important production planning problem is how to best schedule jobs (or lots) when each job consists of a large number of identical parts. This problem is often approached by breaking each job/lot into sublots (termed lot streaming). When the total number of transfer sublots in lot streaming is large
the computational effort to calculate job completion time can be significant. However
researchers have largely neglected this computation time issue. To provide a practical method for production scheduling for this situation
we propose a method to address the
n
-job
m
-machine
and lot streaming flow-shop scheduling problem. We consider the variable sublot sizes
setup time
and the possibility that transfer sublot sizes may be bounded because of capacity constrained transportation activities. The proposed method has three stages: initial lot splitting
job sequencing optimization with efficient calculation of the makespan/total flow time criterion
and transfer adjustment. Computational experiments are conducted to confirm the effectiveness of the three-stage method. The experiments reveal that relative to results reported on lot streaming problems for five standard datasets
the proposed method saves substantial computation time and provides better solutions
especially for large-size problems.
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