Abstract This paper proposes an interesting variant of the parallel machine scheduling problem with sequence-dependent setup times, where a subset of jobs has to be selected to guarantee a minimum profit level while the total completion time is minimized. The problem is addressed under uncertainty, considering both the setup and the processing times as random parameters. To deal with the uncertainty and to hedge against the worst-case performance, a risk-averse distributionally robust approach, based on the conditional value-at-risk measure, is adopted. The computational complexity of the problem is tackled by a hybrid large neighborhood search metaheuristic. The efficiency of the proposed method is tested via computational experiments, performed on a set of benchmark instances.

中文翻译：

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具有作业选择和顺序相关设置时间的分布式鲁棒机器调度问题

摘要 本文提出了并行机调度问题的一个有趣的变体，它具有与序列相关的设置时间，其中必须选择一个作业子集来保证最低利润水平，同时最小化总完成时间。该问题在不确定性下得到解决，将设置和处理时间视为随机参数。为了应对不确定性和对冲最坏情况的表现，采用了一种基于条件风险价值度量的风险规避分布稳健方法。该问题的计算复杂性由混合大型邻域搜索元启发式解决。通过在一组基准实例上执行的计算实验来测试所提出方法的效率。