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Logic-based Benders Decomposition for Alternative Resource Scheduling with Sequence Dependent Setups

机译:基于逻辑的弯曲器分解用于序列依赖性设置的替代资源调度

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We study an unrelated parallel machines scheduling problem with sequence and machine dependent setup times. A logic-based Benders decomposition approach is proposed to minimize the makespan. This approach is a hybrid model that makes use of a mixed integer programming master problem and a specialized solver for travelling salesman subproblems. The master problem is used to assign jobs to machines while the subproblems obtain optimal schedules on each machine given the master problem assignments. Computational results show that the Benders model is able to find optimal solutions up to six orders of magnitude faster as well as solving problems six times the size previously possible with a mixed integer programming model in the literature and twice the size that a branch-and-bound algorithm can solve for similar problems. We further relax the Benders decomposition to accept suboptimal schedules and demonstrate the ability to parameterize solution quality while outperforming state-of-the-art metaheuristics both in terms of solution quality and mean run-time.
机译:我们使用序列和机器相关的设置时间研究一个不相关的并行机调度问题。提出了一种基于逻辑的弯曲器分解方法,以最小化Makespan。这种方法是一种混合模型,它利用混合整数编程主问题以及用于旅行推销员子发布的专业求解器。主题问题用于将作业分配给计算机,而子问题在给定主问题分配给出每台计算机上获得最佳时间表。计算结果表明,弯道模型能够更快地找到最佳解决方案,以及在文献中的混合整数编程模型和分支的两倍于文献中的混合整数编程模型解决问题的最佳解决方案以及解决问题的尺寸六倍。绑定算法可以解决类似的问题。我们进一步放松了弯曲的分解,接受次优的时间表,并展示在解决方案质量和平均运行时表现出优于最先进的综合法的解决方案质量的能力。

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