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Recent approaches to global optimization problems through Particle Swarm Optimization
Authors:Parsopoulos  KE  Vrahatis  MN
Affiliation:(1) Department of Mathematics, University of Patras Artificial Intelligence Research Center (UPAIRC), University of Patras, GR–26110 Patras, Greece
Abstract:This paper presents an overview of our most recent results concerning the Particle Swarm Optimization (PSO) method. Techniques for the alleviation of local minima, and for detecting multiple minimizers are described. Moreover, results on the ability of the PSO in tackling Multiobjective, Minimax, Integer Programming and ell1 errors-in-variables problems, as well as problems in noisy and continuously changing environments, are reported. Finally, a Composite PSO, in which the heuristic parameters of PSO are controlled by a Differential Evolution algorithm during the optimization, is described, and results for many well-known and widely used test functions are given.
Keywords:Differential Evolution  Evolutionary Computation  Global Optimization  Integer Programming  Matlab Code Implementation  Minimax Problems  Multiobjective Optimization  Noisy Problems  Particle Swarm Optimization  Swarm Intelligence
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