Estimation of distribution algorithms with copula-based models

0366053 - ÚI 2012 RIV SK eng C - Konferenční příspěvek (zahraniční konf.)
Bajer, Lukáš - Holeňa, Martin
Estimation of distribution algorithms with copula-based models.
Informačné technológie - aplikácie a teória. Seňa: PONT s.r.o., 2011 - (Lopatková, M.), s. 57-61. ISBN 978-80-89557-01-1.
[ITAT 2011. Conference on Theory and Practice of Information Technologies. Ždiar (SK), 17.09.2011-21.09.2011]
Grant CEP: GA ČR GA201/08/0802
Grant ostatní: GA UK(CZ) 278511/2011
Výzkumný záměr: CEZ:AV0Z10300504
Klíčová slova: estimation of distribution algorithms * copula theory
Kód oboru RIV: IN - Informatika

Estimation of distribution algorithms (EDAs) have been developed as a recent kind of evolutionary algorithms during the last fifteen years. Instead of generating individuals through genetic operations (crossover, mutation), they estimate distribution of solutions with higher fitness evaluation: a model of such distribution is constructed and this model is sampled to obtain a new population. In todays EDA, graphical probabilistic and Gaussian models are used most commonly, which are however either computationally infeasible or unrealistic in many real-world problems. Therefore, other kinds of models are appearing. In this paper copulas are used to construct a model of the distribution of feasible solutions. The copula-based EDA (CEDA) is presented with several kinds of copulas, and brief comparison with standard evolutionary algorithms is provided.
Trvalý link: http://hdl.handle.net/11104/0201147