Novel Adaptive Hybrid Optimization (AHO) Technique Using Biologically-Inspired Algorithms with FLC

A novel adaptive hybrid biologically-inspired algorithm has been proposed in this paper especially for function optimization problems. Four algorithms were studied in the paper, including classical particle swarm optimization (PSO), genetic algorithm (GA), hybrid particle swarm optimizations and hybrid genetic algorithm. The main idea is to incorporate PSO with GA, which can be achieved by a fuzzy logic controller (FLC). Using of a series of benchmark functions (BF) shows that the proposed adaptive hybrid optimization (AHO) possesses a better ability to find the global optimum than the standard PSO algorithm, Genetic algorithm and other hybrid techniques GA-PSO and PSO-GA. For varying series of BF test system parameters, fast acting FLC works as intelligent switching technique agent.