A Modified Particle Swarm Optimization Technique
Luo Xue-chun · Microelectronics & Computer · 2007
In this paper,a modified particle swarm optimization method is proposed.It is compared with the regular particle swarm optimizer(PSO) invented by Kennedy and Eberhart in 1995 based on four different benchmark functions.PSO is motivated by the social behavior of organisms,such as bird flocking and fish schooling.Each particle studies its own previous best solution to the optimization problem,and its group's previous best,and then adjusts its position(solution) accordingly.The optimal value will be found by repeating this process.In the modified PSO proposed here,each particle adjusts its position if the new position improves but makes a decision by some probabilities if it does not.The strategy here is to avoid simply jumping into new position no matter how bad it is.Under all test cases,simulation shows that the modified PSO always finds better solutions than PSO.