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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xinming Zhang Lirong Wang Bingyi Huang |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Computer Science and Technology, Xingtai Vocational and Technical College, Xingtai China (Bingyi Huang) || Harbin Institute of Technology Shenzhen Graduate, School, Shenzhen China (Xinming Zhang; Lirong Wang) |
| Abstract | In this paper, to overcome the premature defect of traditional ant colony algorithm, a new improved niche ant colony algorithm (niche ant colony algorithm based on the fitness sharing principle) is proposed by combining the fitness sharing method with niche ant colony algorithm and applied to the multi-modal function optimization problem. The comparison between the results obtained by the improved niche ant colony algorithm (INACA) and the results found by traditional ant colony algorithm(ACA) and niche genetic algorithm(NGA) shows that the former has higher effectiveness and superiority in global optimization. |
| Starting Page | 403 |
| Ending Page | 406 |
| File Size | 252697 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467324656 |
| e-ISBN | 9781467324670 |
| DOI | 10.1109/MSNA.2012.6324605 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-08-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Computers Fitness sharing Improved niche ant colony algorithm Multi-modal function optimization Heuristic algorithms Educational institutions Gallium nitride Optimization Genetic algorithms |
| Content Type | Text |
| Resource Type | Article |
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