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2010
IEEE

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

10 years 11 months ago
Metropolis Particle Swarm Optimization Algorithm with Mutation Operator for Global Optimization Problems
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. The numerical results show that our approach outperforms several recently published algorithms.
Lhassane Idoumghar, M. Idrissi-Aouad, Mahmoud Melk
Added 13 Feb 2011
Updated 13 Feb 2011
Type Journal
Year 2010
Where ICTAI
Authors Lhassane Idoumghar, M. Idrissi-Aouad, Mahmoud Melkemi, René Schott
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