基于改进蚁群算法的车种代用情况下空车调配优化研究  

The Optimization Of Substitution Of Empty Wagon Distribution Based On Improved Ant Colony Algorithm

作　　者：杨喜娟[1] 王晓峰 张治娟[3] 武福[3] 

机构地区：[1]兰州交通大学电子与信息工程学院,甘肃兰州730070 [2]齐齐哈尔轨道交通装备有限责任公司,黑龙江省齐齐哈尔市161002 [3]甘肃省轨道交通装备系统动力学与可靠性重点实验室(兰州交通大学),甘肃兰州730070

出　　处：《自动化与仪器仪表》2013年第1期17-19,24,共4页Automation & Instrumentation

基　　金：甘肃省自然科学基金资助项目(1112RJZA045)

摘　　要：提出了一种求解车种代用情况下空车调配优化的改进蚁群算法。该算法在迭代过程中,根据求得的最优解的情况自适应的调整信息素挥发度,并通过对选择策略进行改进来增强所得解的多样性,防止解陷入局部最优。将此改进算法用于求解车种代用情况下空车调配优化,建立以行走最短距离为目标函数的空车调配数学模型,并用改进蚁群算法求解此模型。从仿真结果可以看出改进蚁群算法解决此模型时最优解和寻优效率较好,优于基本蚁群算法和标准粒子群算法。An improved Ant Colony Algorithm （ACA） was proposed for substitution of empty wagon distribution. In order to prevent solution into local optimum, the algorithm adjust Pheromone volatility according to optimal solution and improve se- lection strategy to increase the diversity. The improved Ant Colony Algorithm was used to solve the problem of substitution of empty wagon distribution. The mathematic model which minimized the total travelling distance of empty wagon was established and the improved Ant Colony Algorithm was used to solve the model. It was shown by numerical simulation demonstrated that the optimum result and searching performance of improved Ant Colony Algorithm were superior to that of Basic ACA and POS.

关 键 词：铁路 车种代用 空车调配 改进蚁群算法 

分 类 号：TP216[自动化与计算机技术—检测技术与自动化装置]