改进遗传算法在ETV调度优化中的应用研究  

Research on Application of Scheduling Optimization of ETV Based on Improved Genetic Algorithm

作　　者：郭春晖[1] 

机构地区：[1]兰州交通大学机电技术研究所,甘肃兰州730070

出　　处：《物流科技》2015年第10期61-64,69,共5页Logistics Sci-Tech

基　　金：甘肃省自然科学基金项目;项目编号:1208RJZA292

摘　　要：为提高机场货运站中集装货物的出入库效率,以货运站中的核心物流设备升降式转运车(Elevating Transfer Vehicle,ETV)的调度优化问题作为研究对象,通过对遗传算法的改进提升ETV的作业能力。对货运站内的作业过程进行分析,建立ETV柔性启停的五段S型运动模型,基于该模型提出一种改进的遗传算法。针对遗传算法的选择、交叉和变异三个算子,分别提出了基于序的选择算子、基于普莱姆算法的交叉算子和基于随机时间长度的变异算子进行了改进。仿真实验表明,通过改进后的遗传算法对ETV的调度进行优化,缩短了计算时间,提高了全局寻优能力。In order to improve the in-out warehouse efficiency of ULD cargo in airport cargo terminal, as ETV scheduling problem of aviation logistics system as research object, which is the core of logistics equipment, and an improved genetic algorithm was made for it. The process of air cargo station operation are analyzed, we create a new S-shaped mathematical model Considering the flexible start and stop operation for ETC. The model is proposed based on the improved genetic algorithm, eontra posing the three steps of genetic algorithm, then proposed sequence-based selection operator, crossover based minimum cost tree and operator based on a random time cost to use. By comparing the results of simulation experiments with the standard genetic algorithm and improved genetic algorithm, genetic algorithm is improved with better global search ability, and the convergence speed is fast.

关 键 词：升降式转运车 货运站 调度优化 改进遗传算法 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]