A penalty approach to handle inequality constraints in particle swarm optimization

Kazuaki Masuda; Kenzo Kurihara; Eitaro Aiyoshi

doi:10.1109/ICSMC.2010.5641925

A penalty approach to handle inequality constraints in particle swarm optimization

Kazuaki Masuda, Kenzo Kurihara, Eitaro Aiyoshi

Department of Applied Physics and Physico-Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

18 Citations (Scopus)

Abstract

This paper proposes a penalty method for solving nonlinear optimization problems with inequalities by the particle swarm optimization (PSO) algorithm. The proposed method is not only very simple but also useful. One should only search for the global solution of a series of unconstrained minimization problems simply by a standard PSO algorithm. It does not require to check the feasibility of search points during the search. Moreover, it is shown that the global best solution gets feasible as the penalty parameter is increased to a sufficiently but finitely large value. The proposed method is verified by numerical experiments to famous benchmark problems.

Original language	English
Title of host publication	2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Pages	2520-2525
Number of pages	6
DOIs	https://doi.org/10.1109/ICSMC.2010.5641925
Publication status	Published - 2010 Dec 1
Event	2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 - Istanbul, Turkey Duration: 2010 Oct 10 → 2010 Oct 13

Publication series

Name	Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)	1062-922X

Other

Other	2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Country/Territory	Turkey
City	Istanbul
Period	10/10/10 → 10/10/13

Keywords

Constraint handling
Nonlinear programming
Particle swarm optimization (PSO)
Penalty method

ASJC Scopus subject areas

Electrical and Electronic Engineering
Control and Systems Engineering
Human-Computer Interaction

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10.1109/ICSMC.2010.5641925

Cite this

Masuda, K., Kurihara, K., & Aiyoshi, E. (2010). A penalty approach to handle inequality constraints in particle swarm optimization. In 2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 (pp. 2520-2525). [5641925] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). https://doi.org/10.1109/ICSMC.2010.5641925

A penalty approach to handle inequality constraints in particle swarm optimization. / Masuda, Kazuaki; Kurihara, Kenzo; Aiyoshi, Eitaro.

2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010. 2010. p. 2520-2525 5641925 (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Masuda, K, Kurihara, K & Aiyoshi, E 2010, A penalty approach to handle inequality constraints in particle swarm optimization. in 2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010., 5641925, Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, pp. 2520-2525, 2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010, Istanbul, Turkey, 10/10/10. https://doi.org/10.1109/ICSMC.2010.5641925

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AB - This paper proposes a penalty method for solving nonlinear optimization problems with inequalities by the particle swarm optimization (PSO) algorithm. The proposed method is not only very simple but also useful. One should only search for the global solution of a series of unconstrained minimization problems simply by a standard PSO algorithm. It does not require to check the feasibility of search points during the search. Moreover, it is shown that the global best solution gets feasible as the penalty parameter is increased to a sufficiently but finitely large value. The proposed method is verified by numerical experiments to famous benchmark problems.

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A penalty approach to handle inequality constraints in particle swarm optimization

Abstract

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Keywords

ASJC Scopus subject areas

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