We study the quantitative stability of linear multistage stochastic programs under perturbations of the underlying stochastic processes. It is shown that the optimal values behave...
Abstract. Cost-based filtering is a novel approach that combines techniques from Operations Research and Constraint Programming to filter from decision variable domains values that...
Escape analysis can improve the speed and memory efficiency of garbage collected languages by allocating objects to the call stack, but an offline analysis will potentially interf...
Kevin Cleereman, Michelle Cheatham, Krishnaprasad ...
Stochastic programming problems appear as mathematical models for optimization problems under stochastic uncertainty. Most computational approaches for solving such models are base...
We show how a technique from signal processing known as zero-delay convolution can be used to develop more efficient dynamic programming algorithms for a broad class of stochastic...