Mutation-based artificial fish swarm algorithm for bound constrained global opt...

• Author(s): Rocha, Ana Maria A. C. ; Fernandes, Edite Manuela da G. P.
• Date: 2011
• Persistent ID: http://hdl.handle.net/1822/14874
• Origin: RepositóriUM - Universidade do Minho
• Subject(s): Global optimization; Artificial fish swarm; Mutation
• Document Type: Part of book or chapter of book
• Language: English

Description

The herein presented mutation-based artificial fish swarm (AFS) algorithm includes mutation operators to prevent the algorithm to falling into local solutions, diversifying the search, and to accelerate convergence to the global optima. Three mutation strategies are introduced into the AFS algorithm to define the trial points that emerge from random, leaping and searching behaviors. Computational results show that the new algorithm outperforms other well-known global stochastic solution methods.