摘要
研究在给定n个可拆分加工的作业和m台同类不同速加工机器的条件下,考虑同时优化拖期成本和生产能耗的生产调度问题。采用理想点法构建目标函数,建立了考虑拖期成本与能耗的同类并行机排产调度模型。在传统遗传算法基础上,引入多种群、自适应和局部搜索策略以提高搜索效率,并提出个体差异度以改进交叉效果。分别用不同规模的问题进行算例实验,对比改进遗传算法和传统遗传算法性能,求解排产方案。实验结果表明改进算法计算效果优于标准遗传算法,能够求解不同规模该类问题,且具有良好的稳健性。
The scheduling problem that n split activities processed on m uniform parallel machines is studied,considering optimization of both tardiness penalty and production energy consumption.The objective function is constructed by Ideal Point Method(IPM),and the scheduling model of uniform parallel machines considering tardiness penalty and energy consumption is established.On the basis of traditional genetic algorithm,multi-population,adaptive and local search strategy are introduced to improve search efficiency,and individual difference is proposed to improve crossover effects.Numerical experiments are carried out with different scales of problems,and the performance of improved genetic algorithm and traditional genetic algorithm is compared by solving the scheduling scheme.The experimental results show that the improved algorithm performs better than the traditional genetic algorithm and has good robustness.
作者
柳丹丹
龚祝平
邱磊
LIU Dan-dan;GONG Zhu-ping;QIU Lei(School of Business Administration,South China University of Technology,Guangdong Guangzhou510641,China)
出处
《机械设计与制造》
北大核心
2020年第4期262-265,共4页
Machinery Design & Manufacture
基金
国家自然科学基金(71571072)。
关键词
同类并行机
优化调度
遗传算法
作业可拆分
Uniform Parallel Machine
Optimal Scheduling
Genetic Algorithm
Activity Split
