DocumentCode
2331699
Title
A parallel micro-genetic algorithm and its application
Author
Li, Chun-Lian ; Sun, Yu ; Zhang, Li ; Wang, Xi-Cheng
Author_Institution
Sch. of Comput. Sci. & Technol., Changchun Univ., China
Volume
5
fYear
2005
fDate
18-21 Aug. 2005
Firstpage
2880
Abstract
In this paper, the advantage of entropy is analyzed firstly based on the prior information entropy-based genetic algorithm. Then a micro-GA is presented and subsequently introduced its parallel implementation with coarse grain. The so-called micro-GA is a GA with micro-population scheme. Taking advantage of the merit of multi-population, population size can be cut down appropriately by means of inter-population crossover. Because of the inter-population operator, the individuals´ diversity will not turn worse due to the shrunken population size. The parallel strategy comprises a mapping of one (or a few) population(s) onto each processor of MIMD multiprocessing system. Both the micro and parallel approach can speed up the whole genetic evolutionary procedure. Numerical examples and the application in molecular docking show that the proposed method has good accuracy and efficiency.
Keywords
genetic algorithms; multiprocessing systems; parallel algorithms; MIMD multiprocessing system; entropy-based genetic algorithm; genetic evolution; interpopulation crossover; micropopulation; molecular docking; multipopulation; parallel computing; parallel microgenetic algorithm; Algorithm design and analysis; Application software; Computer science; Computer science education; Educational technology; Genetic algorithms; Information analysis; Information entropy; Sun; Testing; Genetic Algorithm; Micro-GA; Molecular Docking; Parallel Computing;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location
Guangzhou, China
Print_ISBN
0-7803-9091-1
Type
conf
DOI
10.1109/ICMLC.2005.1527434
Filename
1527434
Link To Document