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Article type: Research Article
Authors: Trojanowski, Krzysztof
Affiliations: Institute of Computer Science, Polish Academy of Sciences Ordona 21, 01-237, Warszawa, Poland. E-mail: trojanow@ipipan.waw.pl
Abstract: This paper studies properties of a multi-swarm system based on a concept of physical quantum particles (mQSO). Quantum particles differ from the classic ones in the way they move. As opposed to the classic view of particle movement, where motion is controlled by linear kinematic laws, quantum particles change their location according to random distributions. The procedure for generating a new location for the quantum particle is similar to mutation operators widely used in evolutionary computation with real-valued representation. In this paper we study a set of new distributions of candidates for quantum particle location, and we show different features of these distributions. The distributions considered in this paper are divided into two classes: those with a limited range of the new location coordinates and those without such limitations. They are tested on different types of dynamic optimization problems. Experimental verification has been based on a number of testing environments and two main versions of the algorithm: with and without mechanisms protecting against stagnation caused by convergence of sub-swarms during the search process. The experimental results show the advantages of the distribution class, in which the candidates are spread out in the entire search space, and indicate the positive and negative aspects of application of anti-convergencemechanisms.
Keywords: optimization in dynamic environments, particle swarm optimization, tracking optima in dynamic environments, multi-swarm, quantum particles
DOI: 10.3233/FI-2009-154
Journal: Fundamenta Informaticae, vol. 95, no. 2-3, pp. 349-380, 2009
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