基于改进遗传算法的作业车间调度  

Research on Job Shop Scheduling Problem Based on Improved Genetic Algorithm

作　　者：王明 蔡劲草 王雷 

机构地区：[1]安徽工程大学机械与汽车工程学院,安徽芜湖241000

出　　处：《铜仁学院学报》2018年第3期43-46,51,共5页Journal of Tongren University

基　　金：安徽省自然科学基金资助项目(1708085ME129);国家自然科学基金项目(51305001);安徽省高校优秀青年人才支持计划重点项目(gxyq ZD2016125)

摘　　要：针对作业车间调度问题,利用改进遗传算法进行求解以优化调度结果。建立了以完工时间为目标的作业车间调度模型,通过编码、解码,以及复制、交叉、变异等操作,并利用精英保留策略及改进的自适应交叉和变异概率解决作业车间调度问题。通过对MT06基准案例的仿真实验,得到优化调度方案和进化曲线,结果验证了该方法的有效性和可行性。Aiming at the job shop scheduling problem （JSP）, an improved genetic algorithm is used to optimize the scheduling result. The job shop scheduling model with makespan is established. The JSP is solved by setting coding and decoding scheme and selecting genetic operators such as selection, crossover and mutation, and using elitist individual retention strategies and improved adaptive crossover and mutation probabilities. The experiment is tested on the MT06 benchmark problem, the optimal scheduling scheme and evolution curve are obtained. The results verify the effectiveness and feasibility of the proposed method.

关 键 词：作业车间调度 完工时间 自适应遗传算法 精英策略 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]