基于模糊模拟的遗传算法在最短路径问题中的应用  

Application of Genetic Algorithm Based on Fuzzy Simulation in the Shortest Path Problem

作　　者：宁建红[1] 

机构地区：[1]上海电机学院电子信息学院,上海200240

出　　处：《华东理工大学学报（自然科学版）》2007年第B06期137-140,共4页Journal of East China University of Science and Technology

基　　金：基金项目：上海高校选拔培养优秀青年教师科研专项基金

摘　　要：模糊最短路径问题将网络中弧的权值描述成模糊的，突破了传统最短路径问题的局限性，更符合实际网络的要求。采用模糊期望值模型求解最短路径问题，由于模糊变量隶属函数的形式多种多样，对于有些模糊变量，很难求出其具体的期望值，所以本文设计了基于模糊模拟的遗传算法进行求解，获得了良好的效果。In many real systems, the network characters are always variable. In the fuzzy shortest path problem, the weights of network are characterized by general fuzzy variables. When use fuzzy expectation value model to solve the shortest path problem, it is very hard for some fuzzy variables to obtain their expectation value. So the genetic algorithm based on fuzzy simulation is designed. Good effect is achieved.

关 键 词：模糊最短路径 模糊模拟 遗传算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]