A Self-adaptive Genetic Algorithm Based on the Shortest Path Problem

被引：0
|
作者：
Wei, Dong [1 ]
Liu, Zhendong [1 ]
机构：
[1] Shandong Jianzhu Univ, Sch Comp Sci & Technol, Jinan 250101, Peoples R China
来源：
INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND INDUSTRIAL AUTOMATION (ICITIA 2015) | 2015年
关键词：
Shortest Path Problem; Genetic Algorithm; Dynamic Network; A*Algorithm; Dijkstra Algorithm;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In the city, the transportation network is stochastic and dynamic, study of the stochastic shortest path problem are of great value. The paper models the shortest path problem, we use the genetic algorithm in transportation network, and we propose an improved self adaptive genetic algorithm by crossover strategy, selection strategy, and mutation strategy. The paper improved genetic algorithm by adjusting the mutation and crossover parameters. The experiments indicate that the improved genetic algorithm has better result and much higher capacity in global optimization than A* algorithm and Dijkstra algorithm in the shortest path problem.(1)
引用
收藏
页码：362 / 369
页数：8
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