DocumentCode :
515244
Title :
A dynamic multipoint detecting PSO
Author :
Yong, Wang ; Xing, Pang
Author_Institution :
Coll. of Math. & Comput. Sci., Guangxi Univ. for Nat., Nanning, China
Volume :
1
fYear :
2010
fDate :
9-10 Jan. 2010
Firstpage :
474
Lastpage :
479
Abstract :
The chief aim of the present work is to propose a particle swarm optimization(PSO) by using a dynamic multipoint exploring approach. The main technique of this algorithm is that in the preceding phase of the algorithm, every particle can choose its searching direction and its moving velocity independently not being restricted or attracted by the optimal position of which have found by the parcle swarm and makes use of a dynamic multipoint random detecting method. It indicatess, from the empirical results of four typical benchmark functions´ optimization, that the optimization algorithm has the performance of rapid convergence rate, high accurate numerical solution, good stability and powerful robust. This proves that the algorithm is a promising means in solving the complex function optimization problems.
Keywords :
convergence; particle swarm optimisation; benchmark function optimization; dynamic multipoint exploring approach; dynamic multipoint random detecting method; particle swarm optimization; rapid convergence rate; Convergence of numerical methods; Educational institutions; Genetic mutations; Heuristic algorithms; Mathematics; Numerical stability; Particle swarm optimization; Phase detection; Robust stability; Velocity control; Algorithm; Dynamic Explore; Multipoint Detection; Particle Swarm Optimization (PSO);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Logistics Systems and Intelligent Management, 2010 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-7331-1
Type :
conf
DOI :
10.1109/ICLSIM.2010.5461379
Filename :
5461379
Link To Document :
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