Use Fibonacci Numbers to Improve Performance of a Genetic Algorithm (CROSBI ID 658559)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija
Podaci o odgovornosti
Gudelj, Anita ; Kezić, Danko
engleski
Use Fibonacci Numbers to Improve Performance of a Genetic Algorithm
In this paper, we focus on the effect of variable population size on accelerating evolution in the context of our algorithm which integrates MRF1 Petri net with GA. Our approach uses Fibonacci sequence to select the number of individuals in populations. The motivation is to add new individuals when the GA is reaching a stagnation phase and remove individuals when the GA process is progressing well. This variable size population model we tested on some scheduling problems with shared resources. Experimental results confirm that our model finds solutions of similar quality to the ones found by Standard Genetic Algorithm, but with a smaller amount of computational effort.
Genetic algorithm, Petri net, Variable Size Population, Fibonacci sequence
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Podaci o prilogu
1-1.
2014.
objavljeno
Podaci o matičnoj publikaciji
Podaci o skupu
20th Conference of the International Federation of Operational Research Societies IFORS 2014
predavanje
13.07.2014-18.07.2014
Barcelona, Španjolska