Implementation of new hybrid evolutionary algorithm with fuzzy logic control approach for optimization problems

The main purpose of using the hybrid evolutionary algorithm is to reach optimal values and achieve goals that traditional methods cannot because there are different computations, each them has advantages capabilities. Therefore, researchers integrate more than one into a form increase ability these algorithms perform computation when working alone. In this paper, we propose new for genetic (GA) particle swarm optimization (PSO) with fuzzy logic control (FLC) approach function optimization. Fuzzy applied switch dynamically between algorithms, in an attempt improve performance. HEF compared GA, PSO, GAPSO, PSOGA. comparison uses variety measurement functions. addition strongly convex functions, functions can be uniformly distributed or not, valuable evaluating our approach. Iterations 500, 1000, 1500 were used function. algorithm’s efficiency was tested on four often best solution, accounted 75 % all tests. This method superior conventional terms