2 citations · 2 across the 4 of their papers we have counts for
6 papers
Stability of Two-Stage Stochastic Programs Under Problem-Dependent Costs
Nils Peyrousset, Benoît Tran
Classical stability theory for stochastic programming relies on the Wasserstein-Fortet-Mourier duality, which requires the ground cost to be a distance. When using problem-dependen…
Complexity and numerical experiments of a new adaptive generic proximal bundle method
Vincent Guigues, Renato Monteiro, Benoit Tran
This paper develops an adaptive generic proximal bundle method, shows its complexity, and presents numerical experiments comparing this method with two bundle methods on a set of o…
Entropic Regularization of the Nested Distance
Zheng Qu, Benoît Tran
In 2012, Pflug and Pichler proved, under regularity assumptions, that the value function in Multistage Stochastic Programming (MSP) is Lipschitz continuous w.r.t. the Nested Distan…
Minimization Interchange Theorem on Posets
Jean-Philippe Chancelier, Michel de Lara, Benoît Tran
Interchange theorems between minimization and integration are useful in optimization, especially in optimal control and in stochastic optimization. In this article, we establish a…
Tropical Dynamic Programming for Lipschitz Multistage Stochastic Programming
Marianne Akian, Jean-Philippe Chancelier, Benoît Tran
We present an algorithm called Tropical Dynamic Programming (TDP) which builds upper and lower approximations of the Bellman value functions in risk-neutral Multistage Stochastic P…
A stochastic algorithm for deterministic multistage optimization problems
Marianne Akian, Jean-Philippe Chancelier, Benoît Tran
Several attempts to dampen the curse of dimensionnality problem of the Dynamic Programming approach for solving multistage optimization problems have been investigated. One popular…