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首页> 外文期刊>RAIRO Operation Research >METAHEURISTICS TO SOLVE A TASKS SCHEDULING PROBLEM IN PARALLEL IDENTICAL MACHINES WITH UNAVAILABILITY PERIODS
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METAHEURISTICS TO SOLVE A TASKS SCHEDULING PROBLEM IN PARALLEL IDENTICAL MACHINES WITH UNAVAILABILITY PERIODS

机译:解决不可用周期并行机器的任务调度问题的方法论

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摘要

In this paper, we introduce an approach for scheduling problems of n tasks on m identical parallel machines with unavailability periods. This problem is strongly NP-complete which makes finding an optimal solution looks impossible task. In this frame, we suggest a novel heuristic in which availability periods of each machine are filled with the highest weighted tasks. To improve the performance of this heuristic, we have used, on one hand, different diversification strategies with the aim of exploring unvisited regions of the solution space, and on the other hand, two well-known neighborhoods (neighborhood by swapping and neighborhood by insertion). The computational experiment was carried out on three identical parallel machines with different availability periods. It must be mentioned that tasks movement can be within one machine or between different machines. The performance criterion to optimize in this problem is the weighted sum of the end dates of tasks. Note that all data in this problem are integer and deterministic.
机译:在本文中,我们介绍了一种在m个相同的不可用周期的并行计算机上调度n个任务问题的方法。这个问题强烈地是NP完全的,这使得寻找最佳解决方案看起来是不可能的任务。在此框架中,我们提出了一种新颖的启发式方法,其中,每台计算机的可用时间段都充满了权重最高的任务。为了提高这种启发式方法的性能,我们一方面使用了不同的多元化策略,目的是探索解决方案空间中未访问的区域,另一方面,我们使用了两个著名的邻域(通过交换实现邻域,通过插入实现邻域) )。计算实验是在三台相同的具有不同可用时间的并行计算机上进行的。必须提到的是,任务移动可以在一台机器内,也可以在不同机器之间。针对此问题进行优化的性能标准是任务结束日期的加权总和。请注意,此问题中的所有数据都是整数和确定性的。

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