Stochastic Disturbance Particle Swarm Optimization Algorithm Based On Attractive Operator

This paper introduced a stochastic disturbance and an attractive operator into the standard particle swarm optimization (SPSO) algorithm to improve its performance in a predefined number of generations. It termed as stochastic disturbance particle swarm optimization based on attractive operator (SDPSO). In this paper, the concept of attractive operator is recommended that every particle has its own flight direction during the process of optimization, thus it increase the possibility of finding out a potential optimum, moreover, a stochastic disturbance is presented that aim to prevent the particles trapping into local optimum. The experiment results show that the SDPSO algorithm provides better solutions than the SPSO algorithm.