caa a22 4500 445851821 CHVBK 20180317145415.0 cr unu---uuuuu 170323e20111101xx s 000 0 eng 10.1007/s11227-009-0374-6 doi (NATIONALLICENCE)springer-10.1007/s11227-009-0374-6 Parallel evolutionary algorithms based on shared memory programming approaches [Elektronische Daten] [J. Redondo, I. García, P. Ortigosa] In this work, two parallel techniques based on shared memory programming are presented. These models are specially suitable to be applied over evolutionary algorithms. To study their performance, the algorithm UEGO (Universal Evolutionary Global Optimizer) has been chosen. Springer Science+Business Media, LLC, 2009 Evolutionary algorithm nationallicence Shared memory programming nationallicence Computational experiment nationallicence UEGO nationallicence Redondo J. Dpt. Computer Architecture and Electronics, University of Almería, Almeria, Spain aut García I. Dpt. Computer Architecture and Electronics, University of Almería, Almeria, Spain aut Ortigosa P. Dpt. Computer Architecture and Electronics, University of Almería, Almeria, Spain aut The Journal of Supercomputing Springer US; http://www.springer-ny.com 58/2(2011-11-01), 270-279 0920-8542 58:2<270 2011 58 11227 https://doi.org/10.1007/s11227-009-0374-6 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11227-009-0374-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Redondo J. Dpt. Computer Architecture and Electronics, University of Almería, Almeria, Spain aut NATIONALLICENCE 700 1- García I. Dpt. Computer Architecture and Electronics, University of Almería, Almeria, Spain aut NATIONALLICENCE 700 1- Ortigosa P. Dpt. Computer Architecture and Electronics, University of Almería, Almeria, Spain aut NATIONALLICENCE 773 0- The Journal of Supercomputing Springer US; http://www.springer-ny.com 58/2(2011-11-01), 270-279 0920-8542 58:2<270 2011 58 11227 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer