Title :
A gene-constrained genetic algorithm for solving shortest path problem
Author :
Wei, Wu ; Qiuqi, Ruan
Author_Institution :
Inst. of Inf. Sci., Beijing Jiaotong Univ., China
fDate :
31 Aug.-4 Sept. 2004
Abstract :
In this paper, a gene-constrained genetic algorithm (G-C GA) to solve shortest path problem is proposed. In this genetic algorithm (GA), gene is constrained to ensure that each chromosome represents a feasible path without loop during the whole process of search. Contrasting with other genetic algorithm for SP problem, our algorithm can improve the searching capacity with a more accurate solution and more rapid speed of convergence. The G-C GA is more general and flexible no matter in a directed graph or in an undirected graph and it provides the foundation for more complicated shortest path problems.
Keywords :
cellular biophysics; genetic algorithms; genetic engineering; graph theory; chromosome; gene-constrained genetic algorithm; shortest path problem; undirected graph; Artificial intelligence; Artificial neural networks; Biological cells; Encoding; Genetic algorithms; Graph theory; Heuristic algorithms; Information science; Intelligent networks; Shortest path problem;
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN :
0-7803-8406-7
DOI :
10.1109/ICOSP.2004.1442291