基于DE算法求解AGV作业调度问题研究  

Research on Using Differential Evolution Algorithm to Solve the AGV Job Scheduling Problem

作　　者：杨锋英[1] 刘会超[1] 

机构地区：[1]黄淮学院信息工程学院,河南驻马店463000

出　　处：《太原理工大学学报》2014年第4期526-531,共6页Journal of Taiyuan University of Technology

基　　金：河南省科技攻关计划资助项目(112102210383);河南省基础与前沿研究资助项目(122300410071);驻马店市科技攻关计划资助项目(11314)

摘　　要：AGV作业调度问题在一定约束条件下可建模为一个NP完全的多重TSP问题。为了优化AGV作业调度的效果,提高AS/RS系统的运行效率,本文提出用差分演化(DE)算法来求解AGV作业调度问题,并针对问题的特点对DE算法进行了若干改进。设计了新的个体两段编码方法,提出了基于生存时间的种群多样性增强机制来提高算法的搜索能力,避免陷入局部最优等。模拟结果显示,提出的算法可以有效求解AGV作业调度问题,获得了高质量的优化解,且收敛速度快。The AGV job scheduling problem can be modeled as a multiple TSP problem under some constraint conditions,which is also a typical NP complete problem.In order to optimize the results of AGV job scheduling and improve the operation efficiency of the AS/RS system,this paper utilizes the differential evolution（DE）algorithm to solve the AGV job scheduling problem.And some improvements of DE have been made according to the features of the problem.A two segment coding method was designed.The population diversity enhancement mechanism based on the individual survival time was proposed to improve the search ability of the algorithm,and avoid falling into the local optimum.The simulation results show that,the proposed algorithm can effectively solve the AGV job scheduling problem.It not only obtains the high quality optimization solutions,but also gets faster convergence speed.

关 键 词：自动导航小车 作业调度 差分演化 智能算法 多重TSP 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]