Research on Hybrid Algorithm Based on Particle Swarm Optimization and Cuckoo Search Algorithm

For premature convergence and instability of particle Swarm Optimization (PSO) and Cuckoo Search algorithm (CS) in solving function optimization problem, a new hybrid algorithm which based on the combination of PSO and CS is presented. In this algorithm, all individuals are randomly divided into two populations, and the evolutions of two sub-groups are simultaneously performed with different optimization strategies. The information interaction mechanism with last out strategy is introduced to achieve complementary advantages between the algorithm. Finally, the algorithm is put through six benchmark functions and an application example, the results demonstrate that its a powerful global optimization algorithm with rapid convergence rate and high computational precision.