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Unrelated Parallel Machine Selection and Job Scheduling With the Objective of Minimizing Total Workload and Machine Fixed Costs

机译:无关的并行机器选择和作业计划,旨在最大程度地减少总工作量和机器固定成本

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摘要

This paper is concerned with scheduling of a set of n single-operation tasks/orders on a set of m unrelated parallel machines where subcontracting is allowed. When a machine/subcontractor is chosen to do a set of orders/tasks, it incurs a one-time fixed cost. When a job/order is performed by a machine/subcontractor, there is a cost that depends on the machine/subcontractor. The objective is to choose a subset of k machines and/or subcontractors from the set of all m available machines and/or subcontractors to perform all jobs to minimize the sum of total workload costs and total fixed costs. We discuss the complexity of the problem, and prove NP-hardness of the problem. Simplified mathematical development is provided that allows efficient implementation of two-exchange algorithms. An efficient tabu search heuristic with a diversification generation component is developed. An extensive computational experiment of the heuristic for large-scale problems with comparison to the results from CPLEX software is presented. We also solved 40 benchmark k-median problems available on the Internet that have been used by many researchers.
机译:本文涉及在允许分包的m个无关的并行机器上调度n个单操作任务/订单的集合。选择机器/分包商执行一组订单/任务时,将产生一次性的固定成本。当机器/分包商执行工作/订单时,成本取决于机器/分包商。目的是从所有m个可用机器和/或分包商的集合中选择k个机器和/或分包商的子集,以执行所有作业,以最大程度地减少总工作量成本和总固定成本。我们讨论了问题的复杂性,并证明了问题的NP难度。提供简化的数学开发,可以高效实施两次交换算法。开发了一种高效的禁忌搜索启发式方法,具有多样化的生成组件。与CPLEX软件的结果相比,提出了针对大规模问题的启发式方法的广泛计算实验。我们还解决了Internet上存在的40个基准k中值问题,这些问题已被许多研究人员使用。

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