考虑运输时间的柔性作业车间调度问题研究  

Research on Flexible Job-shop Scheduling Problem with Transport Time Consideration

作　　者：杨立熙[1] 余慧慧[1] 

机构地区：[1]福州大学经济与管理学院,福建福州350108

出　　处：《武汉理工大学学报（信息与管理工程版）》2017年第1期104-109,共6页Journal of Wuhan University of Technology：Information & Management Engineering

摘　　要：在实际加工生产中,工序间的运输时间占整个加工时间的比例很大。为了更合理地研究柔性作业车间调度问题,将运输时间作为独立影响因子考虑到模型中。针对模型的特殊性与传统遗传算法易早熟的缺陷,运用小生境的思想和自适应距离变量划分种群并协同进化,进而平衡种群选择压力,避免算法过早收敛至局部最优。同时提出最短工作时间方法优化初始种群,改善算法的求解效率。运用Matlab对国际上通用的算例进行实验并与经典遗传算法对比,结果表明,新提出的算法能够获得更优的调度方案。In actual production, transport time always accounted for a large proportion of entire processing time. In order to study the flexible job shop scheduling problem more reasonably, the transportation time is considered as the independent influence factor. Aiming at the particularity of the model and the shortcomings of the traditional genetic algorithm, the niche habitat and the adaptive distance variable are used to divide the population and co - evolution, so as to balance the population selection pressure and avoid the premature convergence to the local optimum. At the same time, the method of the shortest working time is proposed to optimizing the initial population, then improve the solution efficiency of the algorithm. Using Matlab to test the common inter-national example and compare it with the classical genetic algorithm, the results show that the proposed algorithm on this issue can get a more optimal scheduling scheme.

关 键 词：柔性作业车间调度 运输时间 遗传算法 小生境 选择压力 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]