A GA and Particle Swarm Optimization based hybrid algorithm
Nie Ru, Yue Jianhua · 2008
In this paper an improved particle swarm algorithm is presented firstly and then a hybrid method combining Genetic Algorithm(GA) and Particle Swarm Optimization(PSO) is proposed. This hybrid technique incorporates concepts from GA and PSO and creates individuals in a new generation not only by crossover and mutation operations as found in GA but also by mechanisms of PSO. It can solve the problem of local minimum of the particle swarm optimization and has higher efficiency of search. Simulation results show that the proposed method is effective for the optimization problems.