Enhancing PSO methods for global optimization (Journal article)

Tsoulos, I. G./ Stavrakoudis, A.

The Particle Swarm Optimization (PSO) method is a well-established technique for global optimization. During the past years several variations of the original PSO have been proposed in the relevant literature. Because of the increasing necessity in global optimization methods in almost all fields of science there is a great demand for efficient and fast implementations of relative algorithms. In this work we propose three modi. cations of the original PSO method in order to increase the speed and its efficiency that can be applied independently in almost every PSO variant. These modi. cations are: (a) a new stopping rule, (b) a similarity check and (c) a conditional application of some local search method. The proposed were tested using three popular PSO variants and a variety test functions. We have found that the application of these modi. cations resulted in significant gain in speed and efficiency. (C) 2010 Elsevier Inc. All rights reserved.
Institution and School/Department of submitter: Πανεπιστήμιο Ιωαννίνων. Σχολή Οικονομικών και Κοινωνικών Επιστημών. Τμήμα Οικονομικών Επιστημών
Keywords: global optimization,particle swarm optimization,stochastic methods,stopping rules,particle swarm optimization,differential evolution,multimodal functions,economic-dispatch,genetic algorithm,electromagnetics,generation,power
URI: http://olympias.lib.uoi.gr/jspui/handle/123456789/11213
ISSN: 0096-3003
Link: <Go to ISI>://000278542800020
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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