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首页> 外文期刊>International Journal of Production Research >Bi-objective reentrant hybrid flowshop scheduling: an iterated Pareto greedy algorithm
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Bi-objective reentrant hybrid flowshop scheduling: an iterated Pareto greedy algorithm

机译:双目标可重入混合流水车间调度:迭代帕累托贪心算法

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摘要

The multi-objective reentrant hybrid flowshop scheduling problem (RHFSP) exhibits significance in many industrial applications, but appears under-studied in the literature. In this study, an iterated Pareto greedy (IPG) algorithm is proposed to solve a RHFSP with the bi-objective of minimising makespan and total tardiness. The performance of the proposed IPG algorithm is evaluated by comparing its solutions to existing meta-heuristic algorithms on the same benchmark problem set. Experimental results show that the proposed IPG algorithm significantly outperforms the best available algorithms in terms of the convergence to optimal solutions, the diversity of solutions and the dominance of solutions. The statistical analysis manifestly shows that the proposed IPG algorithm can serve as a new benchmark approach for future research on this extremely challenging scheduling problem.
机译:多目标折返混合流水作业调度问题(RHFSP)在许多工业应用中都具有重要意义,但在文献中却未得到充分研究。在这项研究中,提出了一种迭代帕累托贪婪(IPG)算法来解决RHFSP,其双重目标是最小化制造期和总延迟。通过将其解决方案与相同基准问题集上的现有元启发式算法进行比较,可以评估所提出IPG算法的性能。实验结果表明,所提出的IPG算法在收敛到最优解,解的多样性和解的优势方面明显优于最佳算法。统计分析清楚地表明,所提出的IPG算法可以作为今后对这一极具挑战性的调度问题进行研究的新基准方法。

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