Fuzzy FWA with dynamic adaptation of parameters

We propose in this paper the use fuzzy logic to adjust parameters in the fireworks algorithm (FWA), that is, parameters that usually are considered as constants in the algorithm, we have transformed them to be dynamic parameters in the FWA. First, we realized an exhaustive experimentation of the parameters of the FWA algorithm, with the purpose of selecting the parameters that have more effect on the FWA performance, and we concluded that the main parameters of this algorithm are: numbers of sparks and the explosion amplitude of each firework. The modifications made to these parameters help us provide a better exploration and exploitation abilities to the algorithm. The main goal of this paper is to optimize the performance of the FWA. In this paper, we show the results of the modified algorithm, which we called fuzzy fireworks algorithm and we denoted as FFWA. The results of the experiments were obtained with 6 benchmarks functions.

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