THEORETICAL FRAMEWORK FOR STOCHASTIC PROGRAMMING

This paper aims to present a theoretical framework for stochastic programming models, i.e. for optimization models that involve uncertainty. The framework is characterized by two distinctive features: it is based on the notions of a mathematical program and a probability space. Based on these, it allows the common stochastic programming models to be rigorously derived, and hopefully well understood. Such approach is not common in the literature (See Reference), the stochasticity is generally introduced to a deterministic program after it has been built.