Title :
Repulsive Particle Swarm Optimization based on new diversity
Author :
Niu, Guochao ; Chen, Baodi ; Zeng, Jianchao
Author_Institution :
Software Eng. Inst., Xidian Univ., Xi´´an, China
Abstract :
To avoid the problem of premature convergence, a new diversity-guided Particle Swarm Optimizer (PSO), namely MARPSO is proposed, which is a modification of attractive and repulsive PSO (ARPSO), suggested by Riget and Vesterstorm. A novel measure of population diversity function is presented and a new concept of the particle´s best flight direction is introduced. The simulation test results of four classic functions show that: compared with Standard PSO (BPSO) and ARPSO, MARPSO can effectively increase the diversity of swarm, while maintain a higher convergence speed.
Keywords :
particle swarm optimisation; MARPSO; diversity-guided particle swarm optimizer; particle best flight direction; population diversity function; repulsive PSO; repulsive particle swarm optimization; Computational intelligence; Convergence; Genetic algorithms; Laboratories; Particle measurements; Particle swarm optimization; Simulated annealing; Software engineering; Stochastic processes; Testing; Global Search; Particle Swarm Optimization; Particle´s Best Flight Direction; Population Diversity;
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
DOI :
10.1109/CCDC.2010.5498113