Abstrakt
This thesis presents several contributions of the author to the branch of mathematics called stochastic programming or stochastic optimization. Many real life problems lead to optimization problems where some parts need not to be known precisely, thus they are uncertain.
Stochastic programming provides methods for dealing with uncertainty when it is represented by random variables with a known or estimated probability distribution.
