An Expandable Genetic Cell Array for Global Optimization of Continuous Multimodal Functions

This study presents a simple, fast, accurate, and expandable algorithm with very few parameters for solving global optimization problem of continuous multimodal functions - a calculation unit called cell based on Genetic Algorithm and Particle Swarm is designed. The cell consists of only three chromosomes, among which two of the chromosomes apply crossover operation, and the other chromosome performs Particle Swarm search as the mutation operation. Characteristics of this new method are compared with other hybrid methods. The experimental results on seventeen benchmark functions show the proposed calculation cell can find the optimal solution in fewer function calls than the published GA-PSO hybrid method. Results of multi-cell experiments are presented, and the possibility of incorporating many cells in large searching space is discussed.