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Analysis of a parallel machine scheduling problem with sequence dependent setup times and job availability intervals

机译:分析与序列相关的设置时间和作业可用性间隔的并行机器调度问题

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In this study, we propose constraint programming (CP) model and logic-based Benders algorithms in order to make the best decisions for scheduling non-identical jobs with availability intervals and sequence dependent setup times on unrelated parallel machines in a fixed planning horizon. In this problem, each job has a profit, cost and must be assigned to at most one machine in such a way that total profit is maximized. In addition, the total cost has to be less than or equal to a budget level. Computational tests are performed on a real-life case study prepared in collaboration with the U.S. Army Corps of Engineers (USACE). Our initial investigations show that the pure CP model is very efficient in obtaining good quality feasible solutions but, fails to report the optimal solution for the majority of the problem instances. On the other hand, the two logic-based Benders decomposition algorithms are able to obtain near optimal solutions for 86 instances out of 90 examinees. For the remaining instances, they provide a feasible solution. Further investigations show the high quality of the solutions obtained by the pure CP model. (C) 2015 Elsevier B.V. All rights reserved.
机译:在这项研究中,我们提出了约束编程(CP)模型和基于逻辑的Benders算法,以便为在固定计划范围内的不相关并行机上以可用性间隔和依赖于序列的设置时间来调度不相同的作业做出最佳决策。在这个问题中,每个工作都有利润,成本,并且必须以使总利润最大化的方式最多分配给一台机器。另外,总成本必须小于或等于预算水平。计算测试是在与美国陆军工程兵团(USACE)合作编写的真实案例研究中进行的。我们的初步研究表明,纯CP模型在获得高质量可行解决方案方面非常有效,但是未能报告大多数问题实例的最优解决方案。另一方面,这两种基于逻辑的Benders分解算法能够为90位考生中的86位实例获得接近最优的解决方案。对于其余实例,它们提供了可行的解决方案。进一步的研究表明,通过纯CP模型获得的解决方案的质量很高。 (C)2015 Elsevier B.V.保留所有权利。

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