Hybrid PSO-SA Type Algorithms for Multimodal Function Optimization and Reducing Energy Consumption in Embedded Systems
Joint Authors
Schott, René
Aouad, Maha Idrissi
Idoumghar, Lhassane
Melkemi, Mahmoud
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-06-04
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Abstract EN
The paper presents a novel hybrid evolutionary algorithm that combines Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms.
When a local optimal solution is reached with PSO, all particles gather around it, and escaping from this local optima becomes difficult.
To avoid premature convergence of PSO, we present a new hybrid evolutionary algorithm, called HPSO-SA, based on the idea that PSO ensures fast convergence, while SA brings the search out of local optima because of its strong local-search ability.
The proposed HPSO-SA algorithm is validated on ten standard benchmark multimodal functions for which we obtained significant improvements.
The results are compared with these obtained by existing hybrid PSO-SA algorithms.
In this paper, we provide also two versions of HPSO-SA (sequential and distributed) for minimizing the energy consumption in embedded systems memories.
The two versions, of HPSO-SA, reduce the energy consumption in memories from 76% up to 98% as compared to Tabu Search (TS).
Moreover, the distributed version of HPSO-SA provides execution time saving of about 73% up to 84% on a cluster of 4 PCs.
American Psychological Association (APA)
Idoumghar, Lhassane& Melkemi, Mahmoud& Schott, René& Aouad, Maha Idrissi. 2011. Hybrid PSO-SA Type Algorithms for Multimodal Function Optimization and Reducing Energy Consumption in Embedded Systems. Applied Computational Intelligence and Soft Computing،Vol. 2011, no. 2011, pp.1-12.
https://search.emarefa.net/detail/BIM-448714
Modern Language Association (MLA)
Idoumghar, Lhassane…[et al.]. Hybrid PSO-SA Type Algorithms for Multimodal Function Optimization and Reducing Energy Consumption in Embedded Systems. Applied Computational Intelligence and Soft Computing No. 2011 (2011), pp.1-12.
https://search.emarefa.net/detail/BIM-448714
American Medical Association (AMA)
Idoumghar, Lhassane& Melkemi, Mahmoud& Schott, René& Aouad, Maha Idrissi. Hybrid PSO-SA Type Algorithms for Multimodal Function Optimization and Reducing Energy Consumption in Embedded Systems. Applied Computational Intelligence and Soft Computing. 2011. Vol. 2011, no. 2011, pp.1-12.
https://search.emarefa.net/detail/BIM-448714
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-448714