A fuzzy-controlled Hooke-Jeeves optimization algorithm

This article presents an approach to enhance the Hooke-Jeeves optimization algorithm through the use of fuzzy logic. The Hooke-Jeeves algorithm, similar to many other optimization algorithms, uses predetermined fixed parameters. These parameters do not depend on the objective function values in the current search region. In the proposed algorithm, several fuzzy logic controllers are integrated at the various stages of the algorithm to create a new optimization algorithm: Fuzzy-Controlled Hooke-Jeeves algorithm. The results of this work show that incorporating fuzzy logic in the Hooke-Jeeves algorithm can improve the ability of the algorithm to reach an extremum in different typical optimization test cases and design problems. Sensitivity analysis of the variables of the algorithm is also considered.