具有作业相关存储要求的流水车间调度的 NP-困难和多项式时间可解情况之间的精确边界线

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Alexander Kononov, Marina Pakulich
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引用次数: 0

摘要

我们考虑了两个版本的双机流程车间调度问题,其中每个作业从第一次操作开始到第二次操作结束都需要额外的资源。我们将这种资源称为存储空间。每个作业的存储需求由其第一次操作的处理时间决定。这两个问题在为每个作业分配资源的方式上有所不同。在第一种情况下,作业在开始处理其第一个操作时,会获取所有必要的存储空间单位。在第二种情况下,作业在执行第一个操作时会逐渐占用存储空间。在这两种问题中,我们的目标都是最小化作业时间。在本文中,我们根据存储空间大小和最大操作长度之间的比率,确定了这些问题的 NP-困难和多项式时间可解实例之间的确切边界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An exact borderline between the NP-hard and polynomial-time solvable cases of flow shop scheduling with job-dependent storage requirements

We consider two versions of two-machine flow shop scheduling problems, where each job requires an additional resource from the start of its first operation till the end of its second operation. We refer to this resource as storage space. The storage requirement of each job is determined by the processing time of its first operation. The two problems differ from each other in the way resources are allocated for each job. In the first case, the job captures all the necessary units of storage space at the beginning of processing its first operation. In the second case, the job takes up storage space gradually as its first operation is performed. In both problems, the goal is to minimize the makespan. In our paper, we establish the exact borderline between the NP-hard and polynomial-time solvable instances of the problems with respect to the ratio between the storage size and the maximum operation length.

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来源期刊
Journal of Combinatorial Optimization
Journal of Combinatorial Optimization 数学-计算机:跨学科应用
CiteScore
2.00
自引率
10.00%
发文量
83
审稿时长
6 months
期刊介绍: The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.
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