DocumentCode
3031684
Title
Parallel Evolutionary Computing using a cluster for Mathematical Function Optimization
Author
Valdez, Fevrier ; Melin, Patricia
Author_Institution
Univ. Autonoma de Baja California Tijuana, Tijuana
fYear
2007
fDate
24-27 June 2007
Firstpage
598
Lastpage
603
Abstract
In this paper the optimization of complex mathematical functions is studied, applying evolutionary computing methods (particle swarm optimization and genetic algorithms), with the purpose of finding the global minimum of a search space. The simulations of PSO and GAs were made in a cluster of computers, with the purpose of distributing the function in several processors (slaves) and to gather results in the master.
Keywords
genetic algorithms; particle swarm optimisation; genetic algorithms; mathematical function optimization; parallel evolutionary computing; particle swarm optimization; Acceleration; Computational modeling; Computer simulation; Concurrent computing; Genetic algorithms; Genetic mutations; Optimization methods; Particle swarm optimization; Particle tracking; Power engineering and energy;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 2007. NAFIPS '07. Annual Meeting of the North American
Conference_Location
San Diego, CA
Print_ISBN
1-4244-1213-7
Electronic_ISBN
1-4244-1214-5
Type
conf
DOI
10.1109/NAFIPS.2007.383908
Filename
4271131
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