南京理工大学学报（自然科学版）2017，Vol.41Issue(3)：322-329,8.DOI:10.14177/j.cnki.32-1397n.2017.41.03.008
面向智能制造的作业车间调度算法研究
Job shop scheduling algorithm for intelligent manufacturing
摘要
Abstract
An improved genetic algorithm of intelligent manufacturing for job shop scheduling optimization is proposed to promote the instant responding ability of companys for single piece,small batch,personalized customization.Processes and machines are coded by matrix coding under the constraint condition of multi-workpiece machining process.Selection,crossover and mutation operation corresponding to the coding method are designed,and a retention operator is added to reserve the optimal individual in each generation.Chromosomes are decoded by insert greedy decoding algorithm after the global optimal solution is obtained.The algorithm can optimize multi-workpiece operation planning and machine allocation schemes dynamically based on the shortest processing time or earliness/tardiness penalties minimal expense.Simulation results show the effectiveness.关键词
智能制造/作业车间调度/改进遗传算法/矩阵编码/插入式贪婪解码算法Key words
intelligent manufacturing/job shop scheduling/improved genetic algorithm/matrix coding/insert greedy decoding algorithm分类
信息技术与安全科学引用本文复制引用
彭忆炎,孔建寿,陈轩,王茹..面向智能制造的作业车间调度算法研究[J].南京理工大学学报（自然科学版）,2017,41(3):322-329,8.基金项目
国家科技重大专项(2011ZX04002-051) （2011ZX04002-051）
