改进差分进化算法的作业车间调度优化策略  

Optimization Strategy of Flow Shop Scheduling Based on Improved Differential Evolution Algorithm

作　　者：翁志远[1,2] 方杰[1,2] 孔敏[1,2] 程颖[1] 

机构地区：[1]皖西学院电气与光电工程学院,六安237012 [2]皖西学院智能照明与显示中心,六安237012

出　　处：《控制工程》2017年第6期1282-1285,共4页Control Engineering of China

基　　金：国家自然科学基金青年项目(NO.61302179);安徽省高校优秀青年人才基金重点项目(2013SQRL072ZD);安徽省高校优秀青年人才支持计划重点项目(gxyq ZD2016242);皖西学院自然科学研究重点项目(wxzr201717)

摘　　要：作业车间调度问题是提高企业生产效益的关键技术,为了解决当前作业车间调度问题过程中存在的难题,提出了改进差分进化算法的作业车间调度问题优化算法。首先,将加工最短时间作为评价指标,建立作业车间调度问题优化数学模型;然后,采用差分进化算法对数学模型进行求解,并对差分进化算法进行相应的改进,加快解搜索速度,最后采用实例数据对该算法的性能进行测试和分析。结果表明,所提算法可以得到较好的作业车间调度问题方案,相对于对比算法,搜索结果的评价指标更优,具有更高的实际应用价值。Job shop scheduling is the key technology to improve the production efficiency of enterprises, in order to solve the problems existing in the process of job shop scheduling, a new job shop scheduling optimization method based on the improved differential evolution algorithm is proposed. Firstly, the processing time and waiting time are taken as evaluation indexes, and the mathematical model of job shop scheduling optimization is established. Secondly, the differential evolution algorithm is used to solve the mathematical model, and the differential evolution algorithm is improved to speed up the search speed. Finally, the performance is tested and analyzed by using the data of the instance. The results show that the proposed methods can get better job shop scheduling scheme, the evaluation index is better than other methods, and it has higher practical application value.

关 键 词：车间作业 调度优化 差分进化算法 仿真测试 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]