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Heuristic algorithms for the minmax regret flow-shop problem with interval processing times

机译:minmax的启发式算法使处理时间间隔为间隔的流水车间问题后悔

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摘要

An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete optimization problem is solved. Due to its high complexity, two relaxations are applied to simplify the optimization procedure. First of all, a greedy procedure is used for calculating the criterion’s value, as such calculation is NP-hard problem itself. Moreover, the lower bound is used instead of solving the internal deterministic flow-shop. The constructive heuristic algorithm is applied for the relaxed optimization problem. The algorithm is compared with previously elaborated other heuristic algorithms basing on the evolutionary and the middle interval approaches. The conducted computational experiments showed the advantage of the constructive heuristic algorithm with regards to both the criterion and the time of computations. The Wilcoxon paired-rank statistical test confirmed this conclusion.
机译:考虑了具有无限缓冲区和排列时间作为标准的排列流程的不确定版本。研究的参数不确定性由给定的间隔值处理时间表示。最大的遗憾是用于不确定性的评估。因此,解决了minmax后悔离散优化问题。由于其复杂性高,因此应用了两次松弛以简化优化过程。首先,使用贪婪过程来计算标准的值,因为这种计算本身就是NP难题。此外,使用下限代替求解内部确定性流程。构造性启发式算法适用于松弛优化问题。该算法与先前阐述的其他基于进化和中间区间方法的启发式算法进行了比较。进行的计算实验显示了构造启发式算法在标准和计算时间方面的优势。 Wilcoxon配对统计检验证实了这一结论。

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