A hybrid Niching-based evolutionary PSO for numerical optimization problems
Particle swarm optimization (PSO) is a population-based optimization algorithm which has great potential because of its simplicity and malleability. PSO is a typical global searching heuristic, but there is still an insufficiency in PSO regarding solution exploitation and diversity. In view of this,...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
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2013
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| Online Access: | https://hdl.handle.net/10356/101104 http://hdl.handle.net/10220/16731 |
| _version_ | 1811693930429808640 |
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| author | Hsieh, Tsung-Jung Cheng, Chin-Li Yeh, Wei-Chang |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Hsieh, Tsung-Jung Cheng, Chin-Li Yeh, Wei-Chang |
| author_sort | Hsieh, Tsung-Jung |
| collection | NTU |
| description | Particle swarm optimization (PSO) is a population-based optimization algorithm which has great potential because of its simplicity and malleability. PSO is a typical global searching heuristic, but there is still an insufficiency in PSO regarding solution exploitation and diversity. In view of this, inspired by the pseudo bacterial genetic algorithm (PBGA), we enhance the variety of solution exploitation by incorporating the PBGA process-chromosome mutation. In addition to this, a modified niching method is utilized to preserve the solution diversity, and to avoid premature convergence in search process. We call the proposed algorithm Niching-based Evolutionary PSO (NEPSO). The experimental results test several commonly used numerical benchmark functions, and show that NEPSO has very promising optimization performance. |
| first_indexed | 2024-10-01T06:59:30Z |
| format | Conference Paper |
| id | ntu-10356/101104 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:59:30Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1011042020-05-28T07:17:54Z A hybrid Niching-based evolutionary PSO for numerical optimization problems Hsieh, Tsung-Jung Cheng, Chin-Li Yeh, Wei-Chang School of Computer Engineering IEEE International Conference on Computational Intelligence and Cybernetics (2012 : Bali, Indonesia) DRNTU::Engineering::Computer science and engineering Particle swarm optimization (PSO) is a population-based optimization algorithm which has great potential because of its simplicity and malleability. PSO is a typical global searching heuristic, but there is still an insufficiency in PSO regarding solution exploitation and diversity. In view of this, inspired by the pseudo bacterial genetic algorithm (PBGA), we enhance the variety of solution exploitation by incorporating the PBGA process-chromosome mutation. In addition to this, a modified niching method is utilized to preserve the solution diversity, and to avoid premature convergence in search process. We call the proposed algorithm Niching-based Evolutionary PSO (NEPSO). The experimental results test several commonly used numerical benchmark functions, and show that NEPSO has very promising optimization performance. 2013-10-23T07:10:45Z 2019-12-06T20:33:27Z 2013-10-23T07:10:45Z 2019-12-06T20:33:27Z 2012 2012 Conference Paper Hsieh, T.-J., Cheng, C.-L., & Yeh, W.-C. (2012). A hybrid Niching-based evolutionary PSO for numerical optimization problems. 2012 IEEE International Conference on Computational Intelligence and Cybernetics (CyberneticsCom), 133-137. https://hdl.handle.net/10356/101104 http://hdl.handle.net/10220/16731 10.1109/CyberneticsCom.2012.6381633 en © 2012 IEEE |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Hsieh, Tsung-Jung Cheng, Chin-Li Yeh, Wei-Chang A hybrid Niching-based evolutionary PSO for numerical optimization problems |
| title | A hybrid Niching-based evolutionary PSO for numerical optimization problems |
| title_full | A hybrid Niching-based evolutionary PSO for numerical optimization problems |
| title_fullStr | A hybrid Niching-based evolutionary PSO for numerical optimization problems |
| title_full_unstemmed | A hybrid Niching-based evolutionary PSO for numerical optimization problems |
| title_short | A hybrid Niching-based evolutionary PSO for numerical optimization problems |
| title_sort | hybrid niching based evolutionary pso for numerical optimization problems |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/101104 http://hdl.handle.net/10220/16731 |
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