Hybrid Genetic Algorithm with Particle Swarm Optimization Technique

This paper proposes a new hybrid genetic algorithm which combine with the particle swarm optimization technique in order to improve the search efficiency of classical genetic algorithm. This algorithm gives a new crossover operation and a mutation strategy based on the idea of particle swarm optimization. The experiment results show that the new algorithm can obtain better results than competitive algorithm in the average convergence generation and the global convergence probability.