Overview of artificial fish swarm algorithm and its applications in industrial problems
Artificial fish swarm algorithm (AFSA) is a class of swarm intelligent optimization algorithm stimulated by the various social behaviors of fish in search of food. AFSA can search for global optimum through local optimum value search of each individual fish effectively based on simulating of fish-sw...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/63383/ https://www.scientific.net/AMM.815.253 |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | Artificial fish swarm algorithm (AFSA) is a class of swarm intelligent optimization algorithm stimulated by the various social behaviors of fish in search of food. AFSA can search for global optimum through local optimum value search of each individual fish effectively based on simulating of fish-swarm behaviors such as searching, swarming, following and bulletin. This paper presents an overview of AFSA algorithm by describing the evolution of the algorithm along with all the improvements and its combinations with various algorithms and methods as well as its applications in solving industrial problems. |
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