In this work we focus on efficient heuristics for solving a class of stochastic planning problems that arise in a variety of business, investment, and industrial applications. The...
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision...
In this paper we consider stochastic programming problems where the objective function is given as an expected value of a convex piecewise linear random function. With an optimal s...
Alexander Shapiro, Tito Homem-de-Mello, Joocheol K...
Abstract. We investigate the quality of solutions obtained from sample-average approximations to two-stage stochastic linear programs with recourse. We use a recently developed sof...
— This paper addresses the computational overhead involved in probabilistic reachability computations for a general class of controlled stochastic hybrid systems. An approximate ...
Alessandro Abate, Maria Prandini, John Lygeros, Sh...