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• [P407] On the Intelligence of the Swimming Operators in the Fish School Search Algorithm
  Author(s): Carmelo J. Albanez Bastos-Filho, Fernando Buarque Lima Neto, Maria Fernanda Cavalcanti Sousa, Murilo Rebelo Pontes, S. S. Madeiro
  
  

  Abstract
  Real world engineer problems, for example, times series prediction involve sometimes high dimensional spaces; this makes them hard to compute. A common approach to tackle such challenges is to apply swarm based or evolutionary algorithms. Fish School Search (FSS) is one of such technique that excels on difficult search problems. As FSS is a recent technique only output results where investigate so far. This paper analyzes the influence of the FSS operators on the performance of the algorithm in six benchmark functions. We compared FSS results with some PSO variations and show that all operators are fairly relevant and complementary. Moreover, we assessed the influence of each swimming operator separately. We found that the volitive mechanism is the operator that provides most exploration abilities to the search process. The carried out assessment has also shown that, in average, the best results are obtained only when all the operators are active.

  
   

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