Research on multi-objective flow shop scheduling problem based on improved NSGA-III algorithm

Xi Zhang, Yuxing Wang
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Abstract

Under the background of intelligence, this paper studies the actual workshop scheduling problem of the impeller company. From the perspective of reducing carbon emissions, combining the makespan and total operating cost of the machine as optimization indexes, a multi-objective mathematical model is established. Meanwhile, an improved NSGA-III algorithm was designed to solve the model. Compared with the experimental results of the genetic simulated annealing algorithm, better results were obtained in the three aspects of minimizing carbon emissions, minimizing total operating cost, and shortest completion time, to obtain the optimal scheduling scheme.
基于改进NSGA-III算法的多目标流水车间调度问题研究
本文在智能化背景下,对叶轮公司的实际车间调度问题进行了研究。从减少碳排放的角度出发,结合机器的完工时间和总运行成本作为优化指标,建立了多目标数学模型。同时,设计了一种改进的NSGA-III算法对模型进行求解。与遗传模拟退火算法的实验结果相比,在最小化碳排放、最小化总运行成本和最短完工时间三个方面取得了更好的结果,从而得到最优调度方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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