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Single batch machine scheduling with dual setup times for autoclave molding manufacturing

机译:单批机器调度与高压灭菌成型制造的双重设置时间

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摘要

Batch scheduling involves a machine that can process several jobs simultaneously. The existing literature mainly focuses on the batch-size-dependent setup time. However, setup time depends not only on the batch size but also on technological characteristics. This paper investigates a single batch scheduling problem with dual quantitative and technological setup times extracted from autoclave molding production. A mixed-integer linear programming model (MILP) is established, in which the objective function is to minimize the makespan. The quantitative setup time is linear with the batch size, whereas the technological setup time is nonlinear with the occupied area of all jobs (jobs are represented by rectangles) in a batch. Three lower bounds are presented for evaluating the proposed algorithms. Then, a two-stage approximate algorithm is designed to solve the problem. The first stage concerns the normal batch processing time. In the second stage, an iterative local search method focuses on all terms in the objective function and improves the current solution's quality. Finally, different scales of instances are designed to test the effectiveness and efficiency of the algorithms. Statistical analysis shows that the proposed algorithm in this paper can handle the problem well compared to other algorithms.
机译:批量调度涉及可以同时处理多个作业的机器。现有文献主要侧重于批量依赖于批量的设置时间。但是,设置时间不仅取决于批量大小,还取决于技术特征。本文调查了从高压釜成型生产中提取的双定量和技术设置时间的单批批量调度问题。建立了混合整数线性编程模型(MILP),其中目标函数是最小化MEPESPAN。定量设置时间是线性的,批次大小,而技术设置时间是非线性的,并且在批处理中使用所有作业的占用区域(作业表示作业)。提出了三个下限用于评估所提出的算法。然后,设计了一种两级近似算法来解决问题。第一阶段涉及正常批量处理时间。在第二阶段,迭代本地搜索方法侧重于目标函数中的所有术语,并提高了当前解决方案的质量。最后,旨在测试算法的有效性和效率的不同实例。统计分析表明,与其他算法相比,本文中所提出的算法可以很好地处理问题。

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