Title :
Nonlinear particle swarm optimizer: framework and the implementation of optimization
Author :
Zhihua, Cui ; Jianchao, Zeng
Author_Institution :
Div. of Syst. Simulation & Comput. Application, Taiyuan Univ. of Sci. & Technol., China
Abstract :
Particle swarm optimizer (PSO) is a new evolutionary computation method, which has been successfully applied to many fields. Through mechanism analysis of the standard particle swarm optimizer, a linear equivalent representation of the velocity update equation is given. Thus a new particle swarm optimizer-nonlinear particle swarm optimizer (NPSO) is described in this paper. It can dynamically adjust the limit position that distribute within the ellipse located by the best positions of the population and itself, and drop out of the local minimum point. The simulation results show the correctness and efficiency of the presented methods.
Keywords :
evolutionary computation; limit position; linear equivalent representation; nonlinear particle swarm optimizer; velocity update equation; Computational modeling; Computer applications; Computer simulation; Convergence; Genetics; Neural networks; Nonlinear equations; Optimization methods; Particle swarm optimization; Proposals;
Conference_Titel :
Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th
Print_ISBN :
0-7803-8653-1
DOI :
10.1109/ICARCV.2004.1468829