9 citations · 31 across the 23 of their papers we have counts for
29 papers
Stochastic Quadratic Dynamic Programming
Vincent Guigues, Adriana Washington
We introduce an algorithm called SQDP (Stochastic Quadratic Dynamic Programming) to solve some multistage stochastic optimization problems having strongly convex recourse functions…
A single cut proximal bundle method for stochastic convex composite optimization
Jiaming Liang, Vincent Guigues, Renato D. C. Monteiro
This paper considers optimization problems where the objective is the sum of a function given by an expectation and a closed convex composite function, and proposes stochastic comp…
Operation of an ambulance fleet under uncertainty
Vincent Guigues, Anton Kleywegt, Victor Hugo Nascimento
We introduce two new optimization models for the dispatch of ambulances. The first model, called the ambulance selection problem, is used when an emergency call arrives to decide w…
Risk-Averse Stochastic Optimal Control: an efficiently computable statistical upper bound
Vincent Guigues, Alexander Shapiro, Yi Cheng
In this paper, we discuss an application of the SDDP type algorithm to nested risk-averse formulations of Stochastic Optimal Control (SOC) problems. We propose a construction of a…
On the strong concavity of the dual function of an optimization problem
Vincent Guigues
We provide three new proofs of the strong concavity of the dual function of some convex optimization problems. For problems with nonlinear constraints, we show that the the assumpt…
Constant Depth Decision Rules for multistage optimization under uncertainty
Vincent Guigues, Anatoli Juditsky, Arkadi Nemirovski
In this paper, we introduce a new class of decision rules, referred to as Constant Depth Decision Rules (CDDRs), for multistage optimization under linear constraints with uncertain…