A Novel Particle Swarm Algorithm Based on the Clonel Selection Strategy

The paper proposes a novel neighborhood search operation of particle swarm in the numerical objective space (eg.R n ), 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 swar...

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Bibliographic Details
Main Authors: Haiyan Quan, Xinling Shi
Format: Conference Proceeding
Language:English
Subjects:
Benchmark testing
clonal selection operation
Equations
Gallium
heuristic search
Mathematical model
neighborhood search operation
numerical function optimization
Optimization
Particle swarm optimization
Search problems
swarm algorithm
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Summary:The paper proposes a novel neighborhood search operation of particle swarm in the numerical objective space (eg.R n ), 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.
ISSN:2155-6083
2155-6091
DOI:10.1109/GCIS.2010.20