Title :
A Novel Particle Swarm Algorithm Based on the Clonel Selection Strategy
Author :
Quan, Haiyan ; Shi, Xinling
Author_Institution :
Fac. of Inf. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
Abstract :
The paper proposes a novel neighborhood search operation of particle swarm in the numerical objective space (eg.Rn), and employs the clonal selection strategy which leads the particle swarm to find the optima of the objective space using the neighborhood search operation. So, a novel particle swarm algorithm based on the clonel selection strategy (NPSA/CS) is proposed. In the test experiment, 6 unconstrained benchmark functions are used to demonstrate the performance of NPSA/CS, and compared with CPSO, PSO, GA, DE. The results show that NPSA/CS can find the optimal or close-to-optimal solutions of those benchmark functions efficiently.
Keywords :
numerical analysis; particle swarm optimisation; search problems; NPSA/CS; clonel selection strategy; neighborhood search operation; numerical objective space; numerical optimization problem; particle swarm algorithm; Benchmark testing; Equations; Gallium; Mathematical model; Optimization; Particle swarm optimization; Search problems; clonal selection operation; heuristic search; neighborhood search operation; numerical function optimization; swarm algorithm;
Conference_Titel :
Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9247-3
DOI :
10.1109/GCIS.2010.20