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ASME Press Select Proceedings
Intelligent Engineering Systems through Artificial Neural Networks, Volume 16
ISBN-10:
0791802566
No. of Pages:
1000
Publisher:
ASME Press
Publication date:
2006
eBook Chapter
15 Evaluation of Strategies for Co-Evolutionary Genetic Algorithms: dLCGA Case Study
By
Grégoire Danoy
,
Grégoire Danoy
Faculty of Sciences, Technology and Communications
6, rue R. Coudenhove-Kalergi L-1359 Luxembourg
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Franciszek Seredynski
,
Franciszek Seredynski
Polish-Japanese Institute of Information Technologies
Koszykowa 86 02-008 Warsaw
, Poland
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Pascal Bouvry
Pascal Bouvry
Faculty of Sciences, Technology and Communications
6, rue R. Coudenhove-Kalergi L-1359 Luxembourg
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Page Count:
6
-
Published:2006
Citation
Danoy, G, Seredynski, F, & Bouvry, P. "Evaluation of Strategies for Co-Evolutionary Genetic Algorithms: dLCGA Case Study." Intelligent Engineering Systems through Artificial Neural Networks, Volume 16. Ed. Dagli, CH, Buczak, AL, Enke, DL, Embrechts, M, & Ersoy, O. ASME Press, 2006.
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Dafo, a multi-agent framework dedicated to distributed coevolutionary genetic algorithms (CGAs) is used to evaluate dLCGA, a new dynamic competitive coevolutionary genetic algorithm. We compare the performance of dLCGA to other known classes of CGAs for the Inventory Control Parameter optimization problem (ICP) and in particular show how it improves the results of the static version of LCGA.
Topics:
Genetic algorithms
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