DocumentCode
1651520
Title
Dynamic memory model for non-stationary optimization
Author
Bendtsen, Claus N. ; Krink, Thiemo
Author_Institution
Dept. of Comput. Sci., Aarhus Univ., Denmark
Volume
1
fYear
2002
Firstpage
145
Lastpage
150
Abstract
Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA for two dynamic benchmark problems
Keywords
genetic algorithms; probability; storage management; dynamic benchmark problems; dynamic explicit memory; dynamic memory model; genetic algorithm; nonstationary optimization; repetitive patterns; search landscape; Bioinformatics; Computer science; Control systems; Electrical equipment industry; Elevators; Genetic mutations; Genomics; Industrial control; Job shop scheduling; Routing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location
Honolulu, HI
Print_ISBN
0-7803-7282-4
Type
conf
DOI
10.1109/CEC.2002.1006224
Filename
1006224
Link To Document