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Ant Colony Optimization Algorithm to Parallel Machine Scheduling Problem with Setups

机译:蚁群优化算法与设置的并行机调度问题

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This paper addresses the non-preemptive unrelated parallel machine scheduling problem with machine-dependent and job sequence-dependent setup times. All jobs are available at time zero, all times are deterministic, and the objective is to minimize the makespan. This is a NP-hard problem and in this paper, a two-stage ant colony optimization (ACO) algorithm is introduced and its performance is evaluated by comparing its solutions to the solutions of Tabu Search and an existing heuristic for the same problem. The results show that ACO outperformed the other algorithms.
机译:本文通过机器依赖和作业序列依赖的设置时间解决了非抢占不相关的并行机器调度问题。所有作业都在零时零,始终是确定性的,目标是最小化Makespan。这是一个NP难题,在本文中,引入了两级蚁群优化(ACO)算法,并通过将其解决方案与同一问题的解决方案进行比较来评估其对禁忌搜索解决方案的性能。结果表明,ACO优于其他算法。

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