DocumentCode
175862
Title
A fast genetic algorithm for solving the maximum clique problem
Author
Suqi Zhang ; Jing Wang ; Qing Wu ; Jin Zhan
Author_Institution
Sch. of Inf. Eng., Tianjin Univ. of Commerce, Tianjin, China
fYear
2014
fDate
19-21 Aug. 2014
Firstpage
764
Lastpage
768
Abstract
Aiming at the defects of Genetic Algorithm (GA) for solving the Maximum Clique Problem (MCP) in more complicated, long-running and poor generality, a fast genetic algorithm (FGA) is proposed in this paper. A new chromosome repair method on the degree, elitist selection based on random repairing, uniform crossover and inversion mutation are adopted in the new algorithm. These components can speed up the search and effectively prevent the algorithm from trapping into the local optimum. The algorithm was tested on DIMACS benchmark graphs. Experimental results show that FGA has better performance and high generality.
Keywords
combinatorial mathematics; genetic algorithms; DIMACS benchmark graphs; FGA; MCP; chromosome repair method; combination optimal problem; elitist selection; fast genetic algorithm; inversion mutation; local optimum; maximum clique problem; random repairing; uniform crossover; Benchmark testing; Biological cells; Educational institutions; Genetic algorithms; Maintenance engineering; Sociology; Statistics; chromosome repair; elitist selection; genetic algorithm; inversion mutation; the maximum clique; uniform crossover;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2014 10th International Conference on
Conference_Location
Xiamen
Print_ISBN
978-1-4799-5150-5
Type
conf
DOI
10.1109/ICNC.2014.6975933
Filename
6975933
Link To Document