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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Suqi Zhang Jing Wang Qing Wu Jin Zhan |
| Copyright Year | 2014 |
| Description | Author affiliation: Sch. of Comput., Sci. & Technol., Tianjin Univ., Tianjin, China (Jin Zhan) || Sch. of Comput. Sci. & Software, Hebei Univ. of Technol., Tianjin, China (Jing Wang) || Sch. of Inf. Eng., Tianjin Univ. of Commerce, Tianjin, China (Suqi Zhang) || Sch. of Comput., Sci. & Software, Hebei Univ. of Technol., Tianjin, China (Qing Wu) |
| 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. |
| Starting Page | 764 |
| Ending Page | 768 |
| File Size | 274195 |
| Page Count | 5 |
| File Format | |
| ISSN | 21579563 |
| e-ISBN | 9781479951512 |
| DOI | 10.1109/ICNC.2014.6975933 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-19 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Maintenance engineering Educational institutions Statistics inversion mutation Biological cells Genetic algorithms chromosome repair genetic algorithm the maximum clique Sociology uniform crossover Benchmark testing elitist selection |
| Content Type | Text |
| Resource Type | Article |
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