Iterative fireworks algorithm with fuzzy coefficients
Juan Barraza, Patricia Melín, Fevrier Valdez, Claudia I. González, Oscar Castillo · 2017
Themain aim of this paper is to use fuzzy inference systems for controlling the relevant parameters within the equations of the FWA algorithm. In other words, parameters that are considered constant in the traditional FWA and are now made dynamic by using fuzzy logic. It is worth mentioning that we also made a small modification to the algorithm with the goal of having a better performance and the modification was to change the stopping criteria of the algorithm. In the conventional fireworks algorithm (FWA) the stopping criteria is based on the function evaluations, including, some variations or modifications of the FWA but they also manage this in the same way. We propose a stopping criteria based on the iterations with the goal of having a more precise control and consequently, have a better way to control the output variables in a Fuzzy Inference System (FIS) of Mamdani type, since the number of iterations is used as the input variable. To demonstrate the validity of this modification we tested the algorithm with 12 benchmark functions with good results, and we call the proposed algorithm as Iterative Fuzzy Fireworks Algorithm and we denoted as IFFWA.