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Metaheuristics for identical parallel machines scheduling to minimize mean tardiness

机译:相同并联机器调度以最小化平均迟缓的综合训练

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Scheduling of jobs has been a challenging task in manufacturing and the most real life scheduling problems, which involves multi-objectives and multi-machine environments. This paper presents tabu search and simulated annealing approaches for scheduling jobs on identical parallel machines. The identical parallel machine scheduling problem has been considered to minimize the mean tardiness for the jobs. Initially, an initial solution has been obtained using EDD dispatching rule then, simulated annealing and tabu search have been applied to reach a near optimal solution. Computational experiments are performed on problems with up to 10 machines and 150 jobs. The computational results indicate that the two proposed approaches are capable of obtaining better solutions for the given scheduling problem. Moreover, the tabu search approach provides better solution then simulated annealing approach.
机译:工作安排在制造业和最真实的生活调度问题方面是一个具有挑战性的任务,涉及多目标和多机器环境。本文介绍了在相同的并行机上调度作业的禁忌搜索和模拟退火方法。已经考虑了相同的并行机调度问题以最大限度地减少作业的平均迟到。最初,使用EDD调度规则获得了初始解决方案,因此已应用模拟退火和禁忌搜索来达到近最佳解决方案。对最多10台机器和150个工作的问题进行计算实验。计算结果表明,两种提出的方​​法能够为给定的调度问题获得更好的解决方案。此外,禁忌搜索方法提供更好的解决方案然后模拟退火方法。

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