A naive particle swarm algorithm for constrained optimization problems

In this paper, a naive particle swarm algorithm for constrained optimization problems is proposed. Also, a direct constraint handling method is adopted, which is more direct and easier to be implemented in comparison with other constraint handling methods, such as penalty function, etc. The experime...

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Bibliographic Details
Main Authors: Jin Qin, Benliang Xie
Format: Conference Proceeding
Language:English
Subjects:
Benchmark testing
Constrained Optimization Problem
Constraint Handling
Educational institutions
Equations
Optimization
Particle swarm optimization
Penalty Function
Vectors
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Summary:In this paper, a naive particle swarm algorithm for constrained optimization problems is proposed. Also, a direct constraint handling method is adopted, which is more direct and easier to be implemented in comparison with other constraint handling methods, such as penalty function, etc. The experimental results on benchmark problems show that the proposed algorithm can solve constrained optimization problems effectively and has a robust performance.
ISSN:1948-9439
1948-9447
DOI:10.1109/CCDC.2013.6560892