物流配送路径问题的改进遗传算法与仿真
摘要
通过将物流配送中心的实际物流配送网络描述为由配送中心和顾客两类节点的图,建立了物流配送路径模型.此类问题属于最优化问题,遗传算法是处理此类最优化的有效方法, 本文利用在交叉上采用1致交叉，在变异上采用随机两点变异的改进遗传算法求得图中各节点间的最短路径和最短路径长度,从而得出模型的最优解.改进后的遗传算法能较早地找到满足条件的群体并得到最优解. 通过仿真实例计算,取得了满意的结果。
关键词： 遗传算法； 最优路径选择； 物流； C语言
The improving genetic algorithms and simulation of the logistics distribution routes
Abstract
Through describing the actual logistics distribution network of the logistics distribution center as two nodes figure consisting of distribution center and customer, I established trail models of logistics distribution. Such issues are the optimization problem, Genetic algorithms is a most effective way to deal with such issues. Using the method of a consistent cross in cross and the two point random variation in variation of the improved genetic algorithms can seek the shortest path and the shortest path length between the nodes in the chart and then get the optimum solution. Genetic algorithms can find groups satisfied conditions earlier and get the optimum solution. Through using examples of simulation mathematics achieve satisfactory results.
Key word: genetic algorithm; the optimum path choice; logistics; c language
前言
