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 :
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