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Pruning by dominance in best-first search for the job shop Scheduling problem with total flow time

机译:最佳优先搜索中的优势修剪以总流程时间调度问题

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摘要

Best-First search is a problem solving paradigm that allows to design exact or admissible algorithms. In this paper, we confront the Job Shop Scheduling problem with total flow time minimization by means of the A~* algorithm. We devised a heuristic from a problem relaxation that relies on computing Jackson's preemptive schedules. In order to reduce the effective search space, we formalized a method for pruning nodes based on dominance relations and established a rule to apply this method efficiently during the search. By means of experimental study, we show that the proposed method is more efficient than a genetic algorithm in solving instances with 10 jobs and 5 machines and that pruning by dominance allows A~* to reach optimal schedules, while these instances are not solved by A~* otherwise. These experiments have also made it clear that the Job Shop Scheduling problem with total flow time minimization is harder to solve than the same problem with makespan minimization.
机译:最佳优先搜索是一种解决问题的范例,可以设计精确或可接受的算法。在本文中,我们通过A〜*算法以总流程时间最小化来解决Job Shop调度问题。我们设计了一种启发式问题缓解方法,该方法依赖于计算杰克逊的抢先时间表。为了减少有效的搜索空间,我们正式确定了基于优势关系的修剪节点的方法,并建立了在搜索过程中有效应用该方法的规则。通过实验研究,我们证明了该方法在求解具有10个作业和5台机器的实例时比遗传算法更有效,并且通过优势修剪使A〜*达到最佳调度,而这些实例却无法由A解决〜*否则。这些实验还清楚地表明,总流程时间最小化的Job Shop Scheduling问题比最小化制造时间的相同问题更难解决。

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