Stochastic Programming

John R. Birge

ABSTRACT

Stochastic programming considers models for optimal decision making where certain parameters are not known with certainty. The emphasis in the field is generally on the construction of the models and on the solution of these models to obtain an optimal value, given assumed parameter distributions, or bounds (perhaps with some confidence level) on an optimal value. Due to recent advances in computational capabilities, many applications appear now in finance, transportation, manufacturing, electric power, telecommunications, and other areas. This chapter describes some samples of these applications. It also provides an overview of stochastic programming model formulations and basic computational techniques.