Title :
The random factor in Particle Swarm Optimiazation
Author :
Qiu, Xiaohong ; Liu, Jun ; Ren, Xuemei
Author_Institution :
Sch. of Software, Jiangxi Agric. Univ., Nanchang, China
Abstract :
The paper introduces the random factor in Particle Swarm Optimization. Comparing with inertia weight, the particle´s velocity is determined by previous velocity, own experience, public knowledge and random behavior. The random operator is similar with the mutation operator in the Genetic Algorithms. Simulation results show that the method introducing the random factor is better than inertia weight and constriction factor.
Keywords :
genetic algorithms; particle swarm optimisation; random processes; constriction factor; genetic algorithm; genetic algorithms; inertia weight; mutation operator; particle swarm optimization; particle velocity; random factor; random operator; Control systems; Equations; Evolutionary computation; Genetic algorithms; Genetic mutations; Intelligent control; Intelligent systems; Neural networks; Paper technology; Particle swarm optimization; Particle Swarm Optimization; constriction factor; inertia weight; random operator;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5358027
