Two-machine job shop problem with a single server and sequence-independent non-anticipatory set-up times

IF 0.9 4区 数学 Q3 MATHEMATICS, APPLIED Discrete Optimization Pub Date : 2024-05-28 DOI:10.1016/j.disopt.2024.100845
Nadia Babou , Mourad Boudhar , Djamal Rebaine
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Abstract

We address in this paper the two-machine job shop scheduling problem with a single server that sets up the jobs before they get processed on the machines. The server is only needed during the set-up and becomes free at the end of this phase. Moreover, the set-ups are non-anticipatory and the set-up times are sequence-independent. We seek a schedule that minimizes the overall completion time, also called the makespan. We propose several lower bounds to the problem and prove the NP-hardness in the strong sense of two restricted cases. In addition, we present a linear time algorithm for a special case. In order to solve the general problem, we develop a genetic and simulated annealing algorithms that use feasibility guaranteed procedures. An experimental study is carried out to analyze the performance of these meta-heuristic methods.

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具有单台服务器和与序列无关的非预期准备时间的双机作业车间问题
我们在本文中讨论了双机作业车间调度问题,即在机器上处理作业之前,由一台服务器来设置作业。服务器只在设置过程中需要,在这一阶段结束后就空闲出来。此外,设置是非预期性的,设置时间与顺序无关。我们寻求一种能使整体完成时间(也称为 "makespan")最小化的计划。我们提出了该问题的几个下限,并证明了两个限制情况下强意义上的 "硬度"。此外,我们还针对一种特殊情况提出了一种线性时间算法。为了解决一般问题,我们开发了使用可行性保证程序的遗传和模拟退火算法。我们通过实验研究分析了这些元启发式方法的性能。
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来源期刊
Discrete Optimization
Discrete Optimization 管理科学-应用数学
CiteScore
2.10
自引率
9.10%
发文量
30
审稿时长
>12 weeks
期刊介绍: Discrete Optimization publishes research papers on the mathematical, computational and applied aspects of all areas of integer programming and combinatorial optimization. In addition to reports on mathematical results pertinent to discrete optimization, the journal welcomes submissions on algorithmic developments, computational experiments, and novel applications (in particular, large-scale and real-time applications). The journal also publishes clearly labelled surveys, reviews, short notes, and open problems. Manuscripts submitted for possible publication to Discrete Optimization should report on original research, should not have been previously published, and should not be under consideration for publication by any other journal.
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