DocumentCode
3166071
Title
On optimal population size of genetic algorithms
Author
Alander, Jarmo T.
Author_Institution
Dept. of Comput. Sci., Helsinki Univ. of Technol., Espoo, Finland
fYear
1992
fDate
4-8 May 1992
Firstpage
65
Lastpage
70
Abstract
A description is given of the results of experiments to find the optimum population size for genetic algorithms as a function of problem complexity. It seems that for moderate problem complexity the optimal population size for problems coded as bitstrings is approximately the length of the string in bits for sequential machines. This result is also consistent with earlier experimentation. In parallel architectures the optimal population size is larger than in the corresponding sequential cases, but the exact figures seem to be sensitive to implementation details.<>
Keywords
computational complexity; genetic algorithms; parallel architectures; bitstrings; genetic algorithms; optimum population size; parallel architectures; problem complexity; sequential machines; Computer science; Distributed computing; Genetic algorithms; Information processing; Laboratories; Parallel architectures; Parallel processing; Problem-solving; Robot control; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
CompEuro '92 . 'Computer Systems and Software Engineering',Proceedings.
Conference_Location
The Hague, Netherlands
Print_ISBN
0-8186-2760-3
Type
conf
DOI
10.1109/CMPEUR.1992.218485
Filename
218485
Link To Document