Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization
Artificial immune system (AIS) is one of the natureinspired algorithm for solving optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy can be improved further because the hypermutation in CSA itself c...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Online Access: | http://eprints.utem.edu.my/id/eprint/3973/ http://eprints.utem.edu.my/id/eprint/3973/1/rp058_vol.4-C00778-001.pdf |
| _version_ | 1848886979842801664 |
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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 natureinspired
algorithm for solving optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy
can be improved further because the hypermutation in CSA
itself cannot always guarantee a better solution. Alternatively,Genetic Algorithms (GAs) and Particle Swarm Optimization(PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. In this study, the CSA is modified using the best solution for each exposure (iteration) namely Single Best Remainder (SBR) CSA. In this study, the results show that the performance of the proposed algorithm (SBR-CSA) compares favourably with other algorithms while Half Best Insertion (HBI) CSA produced moderate results in most of the simulations. |
| first_indexed | 2025-11-15T19:47:06Z |
| format | Conference or Workshop Item |
| id | utem-3973 |
| institution | Universiti Teknikal Malaysia Melaka |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:47:06Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utem-39732015-05-28T02:38:56Z http://eprints.utem.edu.my/id/eprint/3973/ Antibody Remainder Method Based Artificial Immune System for 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 natureinspired algorithm for solving optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy can be improved further because the hypermutation in CSA itself cannot always guarantee a better solution. Alternatively,Genetic Algorithms (GAs) and Particle Swarm Optimization(PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. In this study, the CSA is modified using the best solution for each exposure (iteration) namely Single Best Remainder (SBR) CSA. In this study, the results show that the performance of the proposed algorithm (SBR-CSA) compares favourably with other algorithms while Half Best Insertion (HBI) CSA produced moderate results in most of the simulations. 2011 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/3973/1/rp058_vol.4-C00778-001.pdf Yap, David F. W. and Koh, S. P. and Tiong, S. K. (2011) Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization. In: 3rd International Conference on Machine Learning and Computing (ICMLC 2011) , 26-28 Feb 2011, Singapore. http://www.icmlc.org/ |
| spellingShingle | TA Engineering (General). Civil engineering (General) Yap, David F. W. Koh, S. P. Tiong, S. K. Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization |
| title | Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization |
| title_full | Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization |
| title_fullStr | Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization |
| title_full_unstemmed | Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization |
| title_short | Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization |
| title_sort | antibody remainder method based artificial immune system for mathematical function optimization |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://eprints.utem.edu.my/id/eprint/3973/ http://eprints.utem.edu.my/id/eprint/3973/ http://eprints.utem.edu.my/id/eprint/3973/1/rp058_vol.4-C00778-001.pdf |