caa a22 4500 605469075 CHVBK 20210128100320.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00500-014-1368-8 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1368-8 Hybrid PSO6 for hard continuous optimization [Elektronische Daten] [José García-Nieto, Enrique Alba] In our previous works, we empirically showed that a number of $$6_{\pm 2}$$ 6 ± 2 informants may endow particle swarm optimization (PSO) with an optimized learning procedure in comparison with other combinations of informants. In this way, the new version PSO6, that evolves new particles from six informants (neighbors), performs more accurately than other existing versions of PSO and is able to generate good particles for a longer time. Despite this advantage, PSO6 may show certain attraction to local basins derived from its moderate performance on non-separable complex problems (typically observed in PSO versions). In this paper, we incorporate a local search procedure to the PSO6 with the aim of correcting this disadvantage. We compare the performance of our proposal (PSO6-Mtsls) on a set of 40 benchmark functions against that of other PSO versions, as well as against the best recent proposals in the current state of the art (with and without local search). The results support our conjecture that the (quasi)-optimally informed PSO, hybridized with local search mechanisms, reaches a high rate of success on a large number of complex (non-separable) continuous optimization functions. Springer-Verlag Berlin Heidelberg, 2014 Particle swarm optimization nationallicence Fully informed PSO nationallicence Multiple trajectory search nationallicence Benchmarking functions nationallicence García-Nieto José Department of Lenguajes y Ciencias de la Computación, E.T.S.I. Informática, University of Málaga, Campus de Teatinos, 29071, Malaga, Spain aut Alba Enrique Department of Lenguajes y Ciencias de la Computación, E.T.S.I. Informática, University of Málaga, Campus de Teatinos, 29071, Malaga, Spain aut Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1843-1861 1432-7643 19:7<1843 2015 19 500 https://doi.org/10.1007/s00500-014-1368-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1368-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- García-Nieto José Department of Lenguajes y Ciencias de la Computación, E.T.S.I. Informática, University of Málaga, Campus de Teatinos, 29071, Malaga, Spain aut NATIONALLICENCE 700 1- Alba Enrique Department of Lenguajes y Ciencias de la Computación, E.T.S.I. Informática, University of Málaga, Campus de Teatinos, 29071, Malaga, Spain aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1843-1861 1432-7643 19:7<1843 2015 19 500