DocumentCode
2444281
Title
Parallel genetic algorithms with a continuity operator that allows for knowledge inclusion
Author
de Andrés y Toro, B. ; Girón-Sierra, J.M. ; Fernández-Blanco, P. ; De la Cruz, J.M. ; López-Orozco, J.A.
Author_Institution
Complutense Univ., Madrid, Spain
Volume
2
fYear
2000
fDate
2000
Firstpage
1137
Abstract
In recent years we introduced a continuity operator, the “Superindividual”, that allows for the inclusion of knowledge in the evolution of the genetic algorithm. Since we deal with very complex optimization problems, we developed a parallel genetic algorithm, with the Superindividual operator. The paper presents this parallel algorithm, which improves on the results of the conventional genetic algorithm. Two different models of parallel genetic algorithms are compared. The results are very encouraging
Keywords
genetic algorithms; parallel algorithms; Superindividual operator; complex optimization problems; continuity operator; knowledge inclusion; parallel genetic algorithm; Beverage industry; Biomass; Computational efficiency; Ethanol; Fungi; Genetic algorithms; Genetic engineering; Optimization methods; Parallel algorithms; Temperature;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location
La Jolla, CA
Print_ISBN
0-7803-6375-2
Type
conf
DOI
10.1109/CEC.2000.870776
Filename
870776
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