Normative Fish Swarm Algorithm For Global Optimization With Applications
Artificial Fish Swarm Algorithm (AFSA) have become popular optimization technique used to solve various problems, Nevertheless, according to surveys, the existing fish swarm algorithms still have some deficiencies to strike the exact optimum within appropriate convergence rate. Therefore, this work...
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2019
|
| Subjects: | |
| Online Access: | http://eprints.usm.my/48568/ http://eprints.usm.my/48568/1/Normative%20Fish%20Swarm%20Algorithm%20For%20Global%20Optimization%20With%20Applications.pdf |
| _version_ | 1848881191992688640 |
|---|---|
| author | Tan, Weng Hooi |
| author_facet | Tan, Weng Hooi |
| author_sort | Tan, Weng Hooi |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Artificial Fish Swarm Algorithm (AFSA) have become popular optimization technique used to solve various problems, Nevertheless, according to surveys, the existing fish swarm algorithms still have some deficiencies to strike the exact optimum within appropriate convergence rate. Therefore, this work proposes a viable local and global seeking strategy to achieve compelling global optimum at predominant convergence rate. Referred to as Normative Fish Swarm Algorithm
(NFSA), the proposed Fish Swarm Algorithm, Optimized by Particle Swarm Optimization with Extended Memory (PSOEM-FSA) is expanded by amalgamating the normative knowledge to provide supplementary guidelines for better global optimum achievement and convergence rate. NFSA incorporates adjustments of visual, visualmin, step and stepmin parameters to adjust the inconsistency between the prospection and exploitation. In addition, the technique of modified global crossover is incorporated to strengthen the relationship between the candidate solutions. The performance of the NFSA has been tested on ten benchmark functions. The obtained results demonstrated that NFSA accomplished predominant outcomes in terms of optimized solution and convergence speed. Besides that, NFSA has been applied on multi-objective optimization and Maximum Power Point Tracking (MPPT) problems. The results obtained from both applications have proved that the proposed NFSA is more effective in multi-objective optimization and MPPT approaches in comparison to few compared evolutionary algorithms. |
| first_indexed | 2025-11-15T18:15:06Z |
| format | Thesis |
| id | usm-48568 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T18:15:06Z |
| publishDate | 2019 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-485682021-11-17T03:42:10Z http://eprints.usm.my/48568/ Normative Fish Swarm Algorithm For Global Optimization With Applications Tan, Weng Hooi T Technology TK1-9971 Electrical engineering. Electronics. Nuclear engineering Artificial Fish Swarm Algorithm (AFSA) have become popular optimization technique used to solve various problems, Nevertheless, according to surveys, the existing fish swarm algorithms still have some deficiencies to strike the exact optimum within appropriate convergence rate. Therefore, this work proposes a viable local and global seeking strategy to achieve compelling global optimum at predominant convergence rate. Referred to as Normative Fish Swarm Algorithm (NFSA), the proposed Fish Swarm Algorithm, Optimized by Particle Swarm Optimization with Extended Memory (PSOEM-FSA) is expanded by amalgamating the normative knowledge to provide supplementary guidelines for better global optimum achievement and convergence rate. NFSA incorporates adjustments of visual, visualmin, step and stepmin parameters to adjust the inconsistency between the prospection and exploitation. In addition, the technique of modified global crossover is incorporated to strengthen the relationship between the candidate solutions. The performance of the NFSA has been tested on ten benchmark functions. The obtained results demonstrated that NFSA accomplished predominant outcomes in terms of optimized solution and convergence speed. Besides that, NFSA has been applied on multi-objective optimization and Maximum Power Point Tracking (MPPT) problems. The results obtained from both applications have proved that the proposed NFSA is more effective in multi-objective optimization and MPPT approaches in comparison to few compared evolutionary algorithms. 2019-12-01 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/48568/1/Normative%20Fish%20Swarm%20Algorithm%20For%20Global%20Optimization%20With%20Applications.pdf Tan, Weng Hooi (2019) Normative Fish Swarm Algorithm For Global Optimization With Applications. Masters thesis, Universiti Sains Malaysia. |
| spellingShingle | T Technology TK1-9971 Electrical engineering. Electronics. Nuclear engineering Tan, Weng Hooi Normative Fish Swarm Algorithm For Global Optimization With Applications |
| title | Normative Fish Swarm Algorithm For Global Optimization With Applications |
| title_full | Normative Fish Swarm Algorithm For Global Optimization With Applications |
| title_fullStr | Normative Fish Swarm Algorithm For Global Optimization With Applications |
| title_full_unstemmed | Normative Fish Swarm Algorithm For Global Optimization With Applications |
| title_short | Normative Fish Swarm Algorithm For Global Optimization With Applications |
| title_sort | normative fish swarm algorithm for global optimization with applications |
| topic | T Technology TK1-9971 Electrical engineering. Electronics. Nuclear engineering |
| url | http://eprints.usm.my/48568/ http://eprints.usm.my/48568/1/Normative%20Fish%20Swarm%20Algorithm%20For%20Global%20Optimization%20With%20Applications.pdf |