Title :
A Study on the Shortest Path Problem Based on Improved Genetic Algorithm
Author :
Xu, Zongyan ; Li, Haihua ; Guan, Ye
Author_Institution :
Mil. Transp. Dept., Mil. Transp. Univ., Tianjin, China
Abstract :
This paper adresses a shortest path problem in network optimization, and proposes a model with constraints. In order to solve the problem, we present an improved genetic algorithm through optimal selection and crossover strategy of genetic algorithm, and explore the framework and key steps of improved genetic algorithm for solving shortest path problem. This algorithm with advantages of intelligent computation has the strong optimization ability and simple structure, which can handle the constraints easily. The results of experiment demonstrate the effectiveness of the improved genetic algorithm and show the search efficiency and solution quality of the algorithm.
Keywords :
genetic algorithms; network theory (graphs); search problems; crossover strategy; genetic algorithm; intelligent computation; network optimization; optimal selection; optimization ability; search efficiency; shortest path problem; solution quality; Algorithm design and analysis; Biological cells; Genetic algorithms; Optimization; Shortest path problem; Sociology; Statistics; constraints; genetic algorithm; shortest path;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
DOI :
10.1109/ICCIS.2012.52