Title :
Dynamic memory model for non-stationary optimization
Author :
Bendtsen, Claus N. ; Krink, Thiemo
Author_Institution :
Dept. of Comput. Sci., Aarhus Univ., Denmark
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;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1006224
