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Parallel machine selection and job scheduling to minimize machine cost and job tardiness

机译:并行的机器选择和作业计划,以最大程度地减少机器成本和作业时间

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This paper discusses the problem of simultaneously selecting and scheduling parallel machines to minimize the sum of machine holding cost and job tardiness cost. A combinatorial optimization model is developed for this purpose. Solving the developed model is NP-hard. A heuristic algorithm is developed to locate the optimal or near optimal solutions based on a Tabu search mechanism specially designed to control the search process in the solution neighborhood for jobs scheduled on specific machines. Numerical examples show that the solutions of the model lead to compromises between the system cost related to machine selection and the operational cost related to job tardiness penalties. The examples also show that the developed algorithm is effective and computationally efficient.
机译:本文讨论了同时选择和调度并行机器以最小化机器持有成本和作业拖延成本之和的问题。为此,开发了组合优化模型。解决开发的模型是NP难的。基于禁忌搜索机制,开发了一种启发式算法来定位最佳解决方案或接近最佳解决方案,该机制专门设计用于控制在解决方案邻域中针对特定机器上计划的作业的搜索过程。数值示例表明,该模型的解导致折衷与机器选择相关的系统成本与与作业拖延处罚相关的运营成本之间的折衷。实例还表明,所开发的算法是有效的,并且计算效率高。

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