Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States Uncertainties are widespread in the optimization of process systems, such as uncertainties in process ...

This paper gives an algorithm for L-shaped linear programs which arise naturally in optimal control problems with state constraints and stochastic linear programs (which can be represented in this ...

Abstract: Linear programming (LP) is a popular method for optimization of a wide range of applications because of its simplicity and availability. However, LP, in its classic form, is not equipped to ...

In this paper, we introduce an approach for constructing uncertainty sets for robust optimization using new deviation measures for random variables termed the forward and backward deviations. These ...

Abstract: In this paper, we propose two kinds of fuzzy approaches to obtain a satisfactory solution for multiobjective stochastic linear programming problems, in which the criteria of probability ...

ABSTRACT: A technique is developed for finding a closed form expression for the cumulative distribution function of the maximum value of the objective function in a stochastic linear programming ...

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Dynamic stochastic matching problems arise in a variety of recent applications, ranging from ridesharing and online video games to kidney exchange. Such problems are naturally formulated as Markov ...