NDLI: Metropolis Particle Swarm Optimization Algorithm with Mutation Operator for Global Optimization Problems

Content Provider	IEEE Xplore Digital Library
Author	Idoumghar, L. Idrissi-Aouad, M. Melkemi, M. Schott, R.
Copyright Year	2010
Abstract	When a local optimal solution is reached with classical Particle Swarm Optimization (PSO), all particles in the swarm gather around it, and escaping from this local optima becomes difficult. To avoid premature convergence of PSO, we present in this paper a novel variant of PSO algorithm, called MPSOM, that uses Metropolis equation to update local best solutions (lbest) of each particle and uses mutation operator to escape from local optima. The proposed MPSOM algorithm is validated on seven standard benchmark functions and used to solve the problem of reducing memory energy consumption in embedded systems (Scratch-Pad Memories SPMs). The numerical results show that our approach outperforms several recently published algorithms.
Starting Page	35
Ending Page	42
File Size	509675
Page Count	8
File Format	PDF
ISBN	9781424488179
ISSN	10823409
DOI	10.1109/ICTAI.2010.15
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-27
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization Algorithm design and analysis Heuristic algorithms Particle swarm optimization Benchmark testing Equations Convergence Scratch-Pad Memories Particles Swarm Optimization Hybrid Algorithm Global Optimization Benchmark Functions
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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