用约翰逊法则调度多个并行两级流程车间

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Combinatorial Optimization Pub Date : 2024-02-23 DOI:10.1007/s10878-024-01107-z
Guangwei Wu, Fu Zuo, Feng Shi, Jianxin Wang
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引用次数: 0

摘要

众所周知,经典的约翰逊法则(Johnson's Rule)能带来两阶段流程车间的最优调度。然而,目前还不清楚约翰逊法则如何帮助以最小间隔时间为目标,对任意数量的并行两阶段流程车间进行近似排程的算法。因此,我们在本文中研究了这一问题,并提出了一种新的高效算法,该算法将约翰逊法则应用于每个单独的流程车间,并精心设计了流程车间的作业分配流程。该算法的运行时间为(O(n \log n)),近似率为 7/3(其中 n 为作业数量)。与最近针对该问题的 PTAS 结果(Dong 等人,载于 Eur J Oper Res 218(1):16-24,2020 年)相比,我们的算法具有更大的近似率,但从运行时间的角度来看,它在实践中更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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On scheduling multiple parallel two-stage flowshops with Johnson’s Rule

It is well-known that the classical Johnson’s Rule leads to optimal schedules on a two-stage flowshop. However, it is still unclear how Johnson’s Rule would help in approximation algorithms for scheduling an arbitrary number of parallel two-stage flowshops with the objective of minimizing the makespan. Thus within the paper, we study the problem and propose a new efficient algorithm that incorporates Johnson’s Rule applied on each individual flowshop with a carefully designed job assignment process to flowshops. The algorithm is successfully shown to have a runtime \(O(n \log n)\) and an approximation ratio 7/3, where n is the number of jobs. Compared with the recent PTAS result for the problem (Dong et al. in Eur J Oper Res 218(1):16–24, 2020), our algorithm has a larger approximation ratio, but it is more efficient in practice from the perspective of runtime.

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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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