Memetic Algorithm with PSO or BFO´s chemotaxis mechanism as local search for function optimization

Memetic Algorithm (MA) is a metaheuristic search method. In proposed memetic algorithm two memes are used in definite proportion out of total local calls and are applied with random selection. Genetic Algorithm due to its good exploration capability is used as main algorithm and Particle Swarm Optimization (PSO) as well as chemotaxis mechanism of Bacterial Foraging Optimization (BFO) are used as local searches. The memetic process is realized using global best fitness among particles of PSO and by imitating the nutrient information from the bacteria of the best fitness in BFO. The proposed variant of memetic algorithm is tested on the standard benchmark functions with unimodal and multimodal property. When the results are compared, the proposed memetic algorithm shows better performance than MA using PSO (pMA) and MA using BFO (bMA) both in terms of speed of convergence and quality of solutions.