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Improved NSGA-II for energy-efficient distributed no-wait flow-shop with sequence-dependent setup time
Complex & Intelligent Systems ( IF 5.8 ) Pub Date : 2022-08-04 , DOI: 10.1007/s40747-022-00830-6
Qing-qing Zeng, Jun-qing Li, Rong-hao Li, Ti-hao Huang, Yu-yan Han, Hong-yan Sang

This paper addresses a multi-objective energy-efficient scheduling problem of the distributed permutation flowshop with sequence-dependent setup time and no-wait constraints (EEDNWFSP), which have important practical applications. Two objectives minimization of both makespan and total energy consumption (TEC) are considered simultaneously. To address this problem, a new mixed-integer linear programming (MILP) model is formulated. Considering the issues faced in solving large-scale instances, an improved non-dominated sorting genetic algorithm (INSGA-II) is further proposed that uses two variants of the Nawaz-Enscore-Ham heuristic (NEH) to generate high-quality initial population. Moreover, two problem-specific speed adjustment heuristics are presented, which can enhance the qualities of the obtained non-dominated solutions. In addition, four local and two global search operators are designed to improve the exploration and exploitation abilities of the proposed algorithm. The effectiveness of the proposed algorithm was verified using extensive computational tests and comparisons. The experimental results show that the proposed INSGA-II is more effective compared to other efficient multi-objective algorithms.



中文翻译:

改进的 NSGA-II 用于具有与序列相关的设置时间的节能分布式无等待流水车间

本文解决了具有序列相关设置时间和无等待约束的分布式置换流水线(EEDNWFSP)的多目标节能调度问题,具有重要的实际应用。同时考虑了最小化制造时间和总能耗 (TEC) 的两个目标。为了解决这个问题,制定了一种新的混合整数线性规划 (MILP) 模型。考虑到解决大规模实例面临的问题,进一步提出了一种改进的非支配排序遗传算法(INSGA-II),该算法使用 Nawaz-Enscore-Ham 启发式(NEH)的两种变体来生成高质量的初始种群。此外,提出了两种针对特定问题的速度调整启发式方法,可以提高获得的非支配解决方案的质量。此外,四个局部和两个全局搜索算子旨在提高所提出算法的探索和利用能力。通过广泛的计算测试和比较验证了所提出算法的有效性。实验结果表明,与其他高效的多目标算法相比,所提出的 INSGA-II 更有效。

更新日期:2022-08-05
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