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ICMLA
2004

A new discrete binary particle swarm optimization based on learning automata

9 years 5 months ago
A new discrete binary particle swarm optimization based on learning automata
: The particle swarm is one of the most powerful methods for solving global optimization problems. This method is an adaptive algorithm based on social-psychological metaphor. A population of particle adapts by returning stochastically toward previously successful regions in the search space and is influenced by the successes of their topological neighbors. In this paper we propose a learning automata based discrete binary particle swarm algorithm. In the proposed algorithm the set of learning automata assigned to a particle may be viewed as the brain of the particle determining its position from its own and other particles past experience. Simulation results show that the proposed algorithm is a good candidate for solving optimization problems.
Reza Rastegar, Mohammad Reza Meybodi, Kambiz Badie
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where ICMLA
Authors Reza Rastegar, Mohammad Reza Meybodi, Kambiz Badie
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