An improved local best searching in particle swarm optimization using differential evolution

Afnizanfaizal Abdullah; Safaai Deris; Siti Zaiton Mohd Hashim; Mohd Saberi Mohamad; Satya Nanda Vel Arjunan

doi:10.1109/HIS.2011.6122090

An improved local best searching in particle swarm optimization using differential evolution

Afnizanfaizal Abdullah, Safaai Deris, Siti Zaiton Mohd Hashim, Mohd Saberi Mohamad, Satya Nanda Vel Arjunan

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

19 Citations (Scopus)

Abstract

Particle Swarm Optimization (PSO) has achieved remarkable attentions for its capability to solve diverse global optimization problems. However, this method also shows several limitations. PSO easily trapped in the global optimum and often required vast computational cost when solving high dimensional problems. Therefore, we propose some modifications to overcome these issues. In this work, Differential Evolution (DE) mutation and crossover operations are implemented to improve local best particles searching in PSO. A numerical analysis is carried out using benchmark functions and is compared with standard PSO and DE method. Results presented suggest the prospective of our proposed method.

Original language	English
Title of host publication	Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011
Pages	115-120
Number of pages	6
DOIs	https://doi.org/10.1109/HIS.2011.6122090
Publication status	Published - 2011
Externally published	Yes
Event	2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011 - Malacca, Malaysia Duration: Dec 5 2011 → Dec 8 2011

Publication series

Name	Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011

Conference

Conference	2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011
Country/Territory	Malaysia
City	Malacca
Period	12/5/11 → 12/8/11

Keywords

Differential Evolution
Global optimization problems
Hybrid method
Local Best Searching
Particle Swarm Optimization

ASJC Scopus subject areas

Artificial Intelligence
Information Systems

Access to Document

10.1109/HIS.2011.6122090

Cite this

Abdullah, A., Deris, S., Hashim, S. Z. M., Mohamad, M. S., & Arjunan, S. N. V. (2011). An improved local best searching in particle swarm optimization using differential evolution. In Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011 (pp. 115-120). Article 6122090 (Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011). https://doi.org/10.1109/HIS.2011.6122090

An improved local best searching in particle swarm optimization using differential evolution. / Abdullah, Afnizanfaizal; Deris, Safaai; Hashim, Siti Zaiton Mohd et al.
Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011. 2011. p. 115-120 6122090 (Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011).

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

Abdullah, A, Deris, S, Hashim, SZM, Mohamad, MS & Arjunan, SNV 2011, An improved local best searching in particle swarm optimization using differential evolution. in Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011., 6122090, Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011, pp. 115-120, 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011, Malacca, Malaysia, 12/5/11. https://doi.org/10.1109/HIS.2011.6122090

Abdullah A, Deris S, Hashim SZM, Mohamad MS, Arjunan SNV. An improved local best searching in particle swarm optimization using differential evolution. In Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011. 2011. p. 115-120. 6122090. (Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011). doi: 10.1109/HIS.2011.6122090

Abdullah, Afnizanfaizal ; Deris, Safaai ; Hashim, Siti Zaiton Mohd et al. / An improved local best searching in particle swarm optimization using differential evolution. Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011. 2011. pp. 115-120 (Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011).

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title = "An improved local best searching in particle swarm optimization using differential evolution",

abstract = "Particle Swarm Optimization (PSO) has achieved remarkable attentions for its capability to solve diverse global optimization problems. However, this method also shows several limitations. PSO easily trapped in the global optimum and often required vast computational cost when solving high dimensional problems. Therefore, we propose some modifications to overcome these issues. In this work, Differential Evolution (DE) mutation and crossover operations are implemented to improve local best particles searching in PSO. A numerical analysis is carried out using benchmark functions and is compared with standard PSO and DE method. Results presented suggest the prospective of our proposed method.",

keywords = "Differential Evolution, Global optimization problems, Hybrid method, Local Best Searching, Particle Swarm Optimization",

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AU - Arjunan, Satya Nanda Vel

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AB - Particle Swarm Optimization (PSO) has achieved remarkable attentions for its capability to solve diverse global optimization problems. However, this method also shows several limitations. PSO easily trapped in the global optimum and often required vast computational cost when solving high dimensional problems. Therefore, we propose some modifications to overcome these issues. In this work, Differential Evolution (DE) mutation and crossover operations are implemented to improve local best particles searching in PSO. A numerical analysis is carried out using benchmark functions and is compared with standard PSO and DE method. Results presented suggest the prospective of our proposed method.

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An improved local best searching in particle swarm optimization using differential evolution

Abstract

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Keywords

ASJC Scopus subject areas

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