带作业发布日期和拒绝的有界混合批量调度

IF 0.8 4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Operations Research Letters Pub Date : 2024-08-13 DOI:10.1016/j.orl.2024.107159
Jun Xu , Yong-Xing Huang , Daxing Zhang , Ran Lin , Guo-Qiang Fan
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引用次数: 0

摘要

本文研究的是一个有约束的混合批量调度问题,该问题涉及作业发布日期和剔除。机器要处理一批包含多个作业的作业,且作业数量不超过机器容量。对于发布日期一定的情况,我们提出了一种多项式时间精确算法。对于发布日期数量恒定的情况,我们提出了一种伪多项式时间精确算法。对于一般问题,我们提供了一种 2 近似算法和一种多项式时间近似方案。
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Bounded mixed batch scheduling with job release dates and rejection

This paper investigates a bounded mixed batch scheduling problem with job release dates and rejection. The machine processes a batch containing several jobs that their number does not exceed the machine capacity. For the case with a certain release date, we present a polynomial-time exact algorithm. For the case with a constant number of release dates, a pseudo-polynomial-time exact algorithm is proposed. For the general problem, we provide a 2-approximation algorithm and a polynomial-time approximation scheme.

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来源期刊
Operations Research Letters
Operations Research Letters 管理科学-运筹学与管理科学
CiteScore
2.10
自引率
9.10%
发文量
111
审稿时长
83 days
期刊介绍: Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.
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