Verification of calculation efficiency of a new CS-PSO algorithm and its application

Juan Yang, Xuesong Han

Cheng De Petroleum College, Chengde, Hebei, 067000, China 

Intelligent algorithm is developing rapidly with the development of computer technology. And it is widely used in scientific research and industrial application. As a kind of intelligent algorithm, particle swarm optimization (PSO) has been used in solving problem for a long time. It is based on the bird group behaviour and uses biological group model to find the optimal solution. Its advantages are fast calculation speed and easy implementation while the disadvantages are easily getting into the local extreme, slow convergence speed in the late evolutionary and poor precision. In order to avoid the disadvantages, some modification has been studied for PSO algorithm and establishes the concentration degree and steady degree based PSO (CS-PSO) algorithm in the paper. Based on the convergence performance of particle swarm depends on the particle exploration ability, search space has been adaptively adjusted to improve the convergence performance of particle swarm optimization with the variation of optimal fitness value. Corresponding adjusted method has been shown in the paper. According to the example verification, the CS-PSO is effective and then the algorithm is used in the bellow structure optimization.