Fish School Search (FSS), proposed by Bastos Filho and Lima Neto in 2008 is, in its basic version,[1] an unimodal optimization algorithm inspired on the collective behavior of fish schools. The mechanisms of feeding and coordinated movement were used as inspiration to create the search operators. The core idea is to make the fishes “swim” toward the positive gradient in order to “eat” and “gain weight”. Collectively, the heavier fishes have more influence on the search process as a whole, what makes the barycenter of the fish school moves toward better places in the search space over the iterations.[2]
The FSS uses the following principles:[3]
Simple computations in all individuals (i.e. fish)
Various means of storing information (i.e. weights of fish and school barycenter)
Local computations (i.e. swimming is composed of distinct components)
Low communications between neighboring individuals (i.e. fish are to think local but also be socially aware)
Minimum centralized control (mainly for self-controlling of the school radius)
Some distinct diversity mechanisms (this to avoid undesirable flocking behavior)
Scalability (in terms of complexity of the optimization/search tasks)
Autonomy (i.e. ability to self-control functioning)
^C. J. A. B Filho., F. B. de Lima Neto, A. J. C. C.. Lins, A. I. S. Nascimento., and M. P. Lima, "A novel search algorithm based on fish school behavior," Systems, Man and Cybernetics, SMC 2008. IEEE International Conference on, 2008, pp. 2646-2651.
^de Lima Neto, Fernando Buarque, and Marcelo Gomes Pereira de Lacerda. "Multimodal Fish School Search Algorithms Based on Local Information for School Splitting." 2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence. IEEE, 2013
^"FBLN – Prof. Dr. Fernando Buarque de Lima Neto, B.Sc. M.Sc. DIC-Ph.D.(Imperial College/UK) Hab(BR) SM-IEEE(USA) Alexander von Humboldt-Fellow(DE) Academy of Science-Fellow(PE/BR)".
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