DocumentCode :
478067
Title :
Finding a Near-Maximum Independent Set of a Circle Graph by Using Genetic Algorithm with Conditional Genetic Operators
Author :
Wang, Shu-Li ; Wang, Rong-Long ; Chen, Zhi-Qiang ; Okazaki, Kozo
Author_Institution :
Dept. of Comput. Sci., Xinyang Normal Univ., Xinyang
Volume :
1
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
597
Lastpage :
600
Abstract :
The maximum independent set problem is of central importance combinatorial optimization problem. It has many practical applications in science and engineering. In this paper, we propose a genetic algorithm based approach to solve the problem. In the proposed approach, the genetic operators are performed basing on condition instead of probability. The proposed algorithm is tested on a large number of instances and the simulation results show that the proposed method is superior to its competitors.
Keywords :
genetic algorithms; graph theory; set theory; central importance combinatorial optimization problem; circle graph; conditional genetic operators; genetic algorithm; near-maximum independent set; Application software; Codes; Computer science; Genetic algorithms; Geometry; NP-complete problem; RNA; Random number generation; Testing; Very large scale integration; Crossover; Genetic algorithm; Maximum independent set; Mutation; NP-complete;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
Type :
conf
DOI :
10.1109/ICNC.2008.690
Filename :
4666915
Link To Document :
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