Abaev, Pavel - ed. ; Razumchik, Rostislav - ed. ; Kołodziej, Joanna - ed.
We propose a new linkage learning genetic algorithm called the Factor Graph based Genetic Algorithm (FGGA). In the FGGA, a factor graph is used to encode the underlying dependencies between variables of the problem. In order to learn the factor graph from a population of potential solutions, a symmetric non-negative matrix factorization is employed to factorize the matrix of pair-wise dependencies. ; To show the performance of the FGGA, encouraging experimental results on different separable problems are provided as support for the mathematical analysis of the approach. The experiments show that FGGA is capable of learning linkages and solving the optimization problems in polynomial time with a polynomial number of evaluations.
Zielona Góra: Uniwersytet Zielonogórski
AMCS, volume 24, number 3 (2014) ; kliknij tutaj, żeby przejść
Biblioteka Uniwersytetu Zielonogórskiego
2024-04-26
2024-04-26
29
https://zbc.uz.zgora.pl/publication/88786
Nazwa wydania | Data |
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A factor graph based genetic algorithm | 2024-04-26 |
Stavroulaki, Maria E. Stavroulakis, Georgios E. Sofonea, Mircea - ed. Viano, Juan M. - ed.
Ghorbani, Mahsa Ranjbar, S.F. Jurczak, Paweł - red.
Petureau, Louis Doumalin, P. Bremand, Fabrice Jurczak, Paweł - red.
Witkowska, Anna Śmierzchalski, Roman Cordón, Oskar - ed. Kazienko, Przemysław - ed.
Batyrshin, Ildar Wagenknecht, Michael Rutkowska, Danuta - ed. Kacprzyk, Janusz - ed. Zadeh, Lotfi A. - ed.
Witkowska, Anna Tomera, Mirosław Śmierzchalski, Roman Korbicz, Józef (1951- ) - red.
Yan, Fei Dridi, Mahjoub El Moudni, Abdellah Korbicz, Józef (1951- ) - red. Uciński, Dariusz - red.
Schaefer, Robert Byrski, Aleksander Smołka, Maciej Cordón, Oskar - ed. Kazienko, Przemysław - ed.