STOCHASTIC OPTIMIZATION USING INTERVAL ANALYSIS, WITH APPLICATIONS TO PORTFOLIO SELECTION.

In this paper we study a class of optimization problems under uncertainty, with parameters modeled by stochastic random variables. Interval analysis and multiobjective stochastic programming concepts are introduced. Then these two concepts are combined to build a stochastic programming model, with the coefficients of the constraints and the coefficients of the objective function modeled by interval numbers and discrete interval random variables. This model can be used to solve a portfolio optimization problem. [ABSTRACT FROM AUTHOR]