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Title: | MC-PSO/DE hybrid with repulsive strategy - Initial study | ||||||||||
Author: | Pluháček, Michal; Šenkeřík, Roman; Zelinka, Ivan; Davendra, Donald David | ||||||||||
Document type: | Conference paper (English) | ||||||||||
Source document: | Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)Hybrid Artificial Intelligent Systems, HAIS 2015. 2015, vol. 9121, p. 213-220 | ||||||||||
ISSN: | 0302-9743 (Sherpa/RoMEO, JCR) | ||||||||||
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ISBN: | 978-3-319-19643-5 | ||||||||||
DOI: | https://doi.org/10.1007/978-3-319-19644-2_18 | ||||||||||
Abstract: | In this initial study it is described the possible hybridization of advanced Particle Swarm Optimization (PSO) modification called MC-PSO and the Differential evolution (DE) algorithm. The advantage of hybridization of various evolutionary techniques is the shared benefit from various advantages of these methods. The motivation came from previous studies of the MC-PSO performance and behavior. The performance of the proposed method is tested on IEEE CEC 2013 benchmark set and compared with both PSO and DE. © Springer International Publishing Switzerland 2015. | ||||||||||
Full text: | https://link.springer.com/chapter/10.1007/978-3-319-19644-2_18 | ||||||||||
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