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On the convergence of a class of estimation of distribution algorithms

 
: Zhang, Q.; Mühlenbein, H.

:

IEEE Transactions on Evolutionary Computation 8 (2004), Nr.2, S.127-136
ISSN: 1089-778X
Englisch
Zeitschriftenaufsatz
Fraunhofer IAIS ()

Abstract
We investigate the global convergence of estimation of distribution algorithms (EDAs). In EDAs, the distribution is estimated from a set of selected elements, i.e., the parent set, and then the estimated distribution model is used to generate new elements. In this paper, we prove that: 1) if the distribution of the new elements matches that of the parent set exactly, the algorithms will converge to the global optimum under three widely used selection schemes and 2) a factorized distribution algorithm converges globally under proportional selection.

: http://publica.fraunhofer.de/dokumente/N-169991.html