摘要
针对加工速度可变的分布式置换流水车间调度问题,以最大完工时间和机器总能量消耗为优化目标,提出了一种双种群算法.首先,采用混合四种策略的初始化方法来生成高质量的初始种群.其次,针对两个种群的特点分别设计了特定的进化方式,并引入了动态引导因子调整种群的进化方式.同时,提出调速节能策略,进一步优化能量消耗.最后,提出动态种群策略用于平衡两个种群的资源.通过仿真实验证明了各个策略的有效性,并与其他算法进行了对比,结果表明所提出的算法具有明显的优越性.
Aiming at the distributed permutation flowshop scheduling problem with variable processing speed,a dual-population algorithm is proposed to optimize the makespan and the total energy consumption of the machine.First,an initialization method that mixes four strategies is used to generate a high-quality initial population.Second,specific evolution methods are designed according to the characteristics of the two populations,and the dynamic guide factor is introduced to adjust the evolution mode of the populations.Meanwhile,an energy-saving strategy for speed regulation is proposed to further optimize energy consumption.Finally,a dynamic population strategy is proposed to balance the resources of the two populations.Simulation results verify the effectiveness of each strategy,and show that the proposed dual population algorithm outperforms current multi-objective evolutionary algorithms.
作者
曾亮
石俊洋
胡迈
李明
ZENG Liang;SHI Junyang;HU Mai;LI Ming(School of Electrical and Electronic Engineering,Hubei University of Technology,Wuhan 430068,China)
出处
《南京信息工程大学学报》
CAS
北大核心
2024年第6期782-790,共9页
Journal of Nanjing University of Information Science & Technology
基金
国家重点研发计划项目(2018YFC0116100)
湖北省教育厅科学研究计划重点项目(D20211402)
湖北省重点研发计划项目(2020BAB114,2023BAB094)。
关键词
置换流水车间
双种群算法
分布式
变速车间
多目标优化
permutation flowshop
dual-population algorithm
distributed
variable speed shop
multi-objective optimization
