Necessary and sufficient optimality conditions for two-stage stochastic programming problems
Vlasta Kaňková (1989)
Kybernetika
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Vlasta Kaňková (1989)
Kybernetika
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Vlasta Kaňková (1997)
Kybernetika
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Vlasta Kaňková (2010)
Kybernetika
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“Classical” optimization problems depending on a probability measure belong mostly to nonlinear deterministic optimization problems that are, from the numerical point of view, relatively complicated. On the other hand, these problems fulfil very often assumptions giving a possibility to replace the “underlying” probability measure by an empirical one to obtain “good” empirical estimates of the optimal value and the optimal solution. Convergence rate of these estimates have been studied...
Antonio Heras Martínez, Ana García Aguado (1998)
Revista de la Real Academia de Ciencias Exactas Físicas y Naturales
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In this article we discuss several alternative formulations for Stochastic Goal Programming. Only one of these models, which is a particular case of the Stochastic Programs with Recourse, is also compatible with Bayesian Decision Theory. Moreover, it is posible to approximate its solutions by means of an iterative algorithm.