DocumentCode :
2978735
Title :
A study of a non-linear optimization problem using a distributed genetic algorithm
Author :
Neves, Nuno ; Nguyen, Anthony-Trung ; Torres, Edgar L.
Author_Institution :
Illinois Univ., Champaign, IL, USA
Volume :
2
fYear :
1996
fDate :
12-16 Aug 1996
Firstpage :
29
Abstract :
Genetic algorithms have been used successfully as a global optimization method when the search space is very large. To characterize and analyze the performance of genetic algorithms on a cluster of workstations, a parallel version of the GENESIS 5.0 was developed using PVM 3.3. This version, called VMGENESIS, was used to study a nonlinear least-squares problem. Performance results show that linear speedups can be achieved if the basic distributed genetic algorithm is combined with a simple dynamic load-balancing mechanism. Results also show that the quality of search changes significantly with the number of processors involved in the computation and with the frequency of communication
Keywords :
distributed algorithms; genetic algorithms; least squares approximations; performance evaluation; simulated annealing; GENESIS 5.0; PVM 3.3; VMGENESIS; distributed genetic algorithm; nonlinear least-squares problem; nonlinear optimization problem; performance results; search space; Algorithm design and analysis; Clustering algorithms; Concurrent computing; Dissolved gas analysis; Frequency; Genetic algorithms; Numerical analysis; Optimization methods; Simulated annealing; Workstations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Processing, 1996. Vol.3. Software., Proceedings of the 1996 International Conference on
Conference_Location :
Ithaca, NY
ISSN :
0190-3918
Print_ISBN :
0-8186-7623-X
Type :
conf
DOI :
10.1109/ICPP.1996.537378
Filename :
537378
Link To Document :
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