A filter-based artificial fish swarm algorithm for constrained global optimization: theoretical and practical issues
This paper presents a filter-based artificial fish swarm algorithm for solving non- convex constrained global optimization problems. Convergence to an ε-global minimizer is guaranteed. At each iteration k, the algorithm requires a (ρ(k),ε(k))-global minimizer of a bound constrained bi-objective subprob...
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| Outros Autores: | , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2014
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/1822/30773 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/30773 |