DocumentCode
342872
Title
Enhancing transposition performance
Author
Simões, Anabela Borges ; Costa, Ernesto
Author_Institution
Centre for Inf. & Syst., Coimbra Univ., Portugal
Volume
2
fYear
1999
fDate
1999
Abstract
Transposition is a new genetic operator alternative to crossover and allows a classical GA to achieve better results. This mechanism characterized by the presence of mobile genetic units must be used with the right parameters to enable maximum performance to the GA. The paper presents the results of an empirical study which offers the main guidelines to choose the proper setting of parameters to use with transposition, which will lead the GA to the best solutions
Keywords
genetic algorithms; search problems; classical GA; crossover; genetic operator; maximum performance; mobile genetic units; transposition performance; Biological materials; Biological processes; Evolution (biology); Evolutionary computation; Genetic algorithms; Genetic mutations; Guidelines; Informatics; Microorganisms; Mobile robots;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on
Conference_Location
Washington, DC
Print_ISBN
0-7803-5536-9
Type
conf
DOI
10.1109/CEC.1999.782651
Filename
782651
Link To Document