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Use Fibonacci Numbers to Improve Performance of a Genetic Algorithm (CROSBI ID 658559)

Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija

Gudelj, Anita ; Kezić, Danko Use Fibonacci Numbers to Improve Performance of a Genetic Algorithm. 2014. str. 1-1

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

Povezanost rada

Informacijske i komunikacijske znanosti, Tehnologija prometa i transport