Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization
Artificial immune system (AIS) is one of the nature-inspired algorithm for solving optimization problems. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability compare to other meta-heuristic methods. However, the CSA rate of convergence and accuracy can be further imp...
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| Format: | Article |
| Language: | English |
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IDOSI Publications
2011
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| Online Access: | http://eprints.utem.edu.my/id/eprint/3970/ http://eprints.utem.edu.my/id/eprint/3970/1/10.pdf |
| _version_ | 1848886979292299264 |
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| author | Yap, David F. W. Koh, S. P. Tiong, S. K. |
| author_facet | Yap, David F. W. Koh, S. P. Tiong, S. K. |
| author_sort | Yap, David F. W. |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | Artificial immune system (AIS) is one of the nature-inspired algorithm for solving optimization problems. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability compare to other meta-heuristic methods. However, the CSA rate of convergence and accuracy can be further improved as the hypermutation in CSA itself cannot always guarantee a better solution. Conversely, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have an inclination to converge prematurely. In this work, the CSA is modified using the best solutions for each exposure (iteration) namely Single Best Remainder (SBR) - CSA. Simulation results show that the proposed algorithm is able to enhance the performance of the conventional CSA in terms of accuracy and stability for single objective functions. |
| first_indexed | 2025-11-15T19:47:06Z |
| format | Article |
| id | utem-3970 |
| institution | Universiti Teknikal Malaysia Melaka |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:47:06Z |
| publishDate | 2011 |
| publisher | IDOSI Publications |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utem-39702021-12-23T16:49:32Z http://eprints.utem.edu.my/id/eprint/3970/ Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization Yap, David F. W. Koh, S. P. Tiong, S. K. TA Engineering (General). Civil engineering (General) Artificial immune system (AIS) is one of the nature-inspired algorithm for solving optimization problems. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability compare to other meta-heuristic methods. However, the CSA rate of convergence and accuracy can be further improved as the hypermutation in CSA itself cannot always guarantee a better solution. Conversely, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have an inclination to converge prematurely. In this work, the CSA is modified using the best solutions for each exposure (iteration) namely Single Best Remainder (SBR) - CSA. Simulation results show that the proposed algorithm is able to enhance the performance of the conventional CSA in terms of accuracy and stability for single objective functions. IDOSI Publications 2011 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/3970/1/10.pdf Yap, David F. W. and Koh, S. P. and Tiong, S. K. (2011) Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization. World Applied Sciences Journal, 14 (10). pp. 1507-1514. ISSN 1818-4952 http://www.idosi.org/wasj/wasj.htm none |
| spellingShingle | TA Engineering (General). Civil engineering (General) Yap, David F. W. Koh, S. P. Tiong, S. K. Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization |
| title | Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization |
| title_full | Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization |
| title_fullStr | Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization |
| title_full_unstemmed | Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization |
| title_short | Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization |
| title_sort | artificial immune system based remainder method for multimodal mathematical function optimization |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://eprints.utem.edu.my/id/eprint/3970/ http://eprints.utem.edu.my/id/eprint/3970/ http://eprints.utem.edu.my/id/eprint/3970/ http://eprints.utem.edu.my/id/eprint/3970/1/10.pdf |