摘要
研究由多个加工站、一个集中物料存储区和一台自动引导小车(AGV)组成的协同制造系统调度问题。针对该调度问题,建立了工件和AGV调度集成的数学模型。提出一种改进的混合遗传算法,在标准遗传算法的基础上引入模拟退火算法的Boltzmann生存机制,加快了算法收敛速度,克服了遗传算法过早收敛的缺陷,同时对算法的变异、交叉算子和更新机制进行了改进。仿真实验表明,改进的混合遗传算法能有效优化作业顺序和AGV行走路径,为具有AGV约束的柔性生产调度提供一种有效的实践途径。
Based on the Collaborative Manufacturing System（ CMS） consisting of multiple processing stations,a centralized storage area and an Automatic Guided Vehicle（ AGV）,a mathematical model was built on analysis of the resource constrained problem. The architecture of a dispatching approach with hybrid genetic algorithm was proposed to solve the scheduling problem under resource constraint of the single AGV. This modified hybrid genetic algorithm improved the method of coding,crossover and mutation,which can optimize the job＇s machining sequence and the action sequences of AGV movement effectively. Finally,the simulation experiment results in CMS showed that the proposed method is feasible for the integrated scheduling for CMS with the AGV constraint.
出处
《电子科技》
2016年第6期29-33,共5页
Electronic Science and Technology
关键词
混合遗传算法
自动引导小车
生产调度
协同制造系统
计算机仿真
hybrid genetic algorithm
automatic guided vehicle
production scheduling
collaborative manufacturing system
computer simulation
