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Comparison of heuristics for flowtime minimisation in permutation flowshops

机译:置换流水车间中用于最小化流时间的启发式方法的比较

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In this paper, we address the problem of sequencing jobs in a permutation flow shop with the objective of minimising the sum of completion times or flowtime. This objective is considered to be relevant and meaningful for today's dynamic production environment, and therefore it has attracted the attention of researchers during the last years. As a result, a number of different types of heuristics have recently been developed, each one claiming to be the best for the problem. However, some of these heuristics have been independently developed and only partial comparisons among them exist. Consequently, there are no conclusive results on their relative performance. Besides, some of these types of heuristics are of a different nature and could be combined in order to obtain composite heuristics. In this paper, we first classify and conduct an extensive comparison among the existing heuristics. Secondly, based on the results of the experiments, we suggest two new composite heuristics for the problem. The subsequent computational experience shows these two heuristics to be efficient for the problem under consideration.
机译:在本文中,我们以最小化完成时间或流程时间的总和为目标,解决排列流程车间中的作业排序问题。该目标被认为与当今动态生产环境相关且有意义,因此在最近几年中吸引了研究人员的注意力。结果,最近开发了许多不同类型的启发式方法,每一种都被认为是解决该问题的最佳方法。但是,其中一些启发式方法是独立开发的,它们之间仅存在部分比较。因此,它们的相对性能没有结论性的结果。此外,其中某些类型的启发式方法具有不同的性质,可以进行组合以获得组合启发式方法。在本文中,我们首先对现有的启发式方法进行分类并进行广泛的比较。其次,根据实验结果,我们针对该问题提出了两种新的组合启发式方法。随后的计算经验表明,这两种启发式方法对于所考虑的问题是有效的。

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