Particle Swarm Optimization Based on the Sine CarrierWave

The traditional PSO algorithm(TPSO) is easily trapped in the local optimum and converges slowly. Coping with the above shortcomings, a novel PSO algorithm based on the carrierwave, CarrierWave PSO (CWPSO) is presented in this paper. By means of the sine wave's character that the value domain is steady while the independent variable is continuously changing, the CWPSO algorithm uses the changing independent variables of every carrierwaves to fix the positions of every particle so as to obviously improve the global searching ability. At the same time, for the possible extreme points, a precise search process based on the carrierwave extending is taken. By the simulation on a series of benchmark functions, it is shown that the CWPSO algorithm can not only find all the optimum values, but also spends only about 1/3 to 1/5 times as the TPSO and LWPSO algorithms. Furthermore, the CWPSO algorithm is not sensitive to the dimensions of the optimumsearching problems such that the applied field is greatly enlarged.