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pro vyhledávání: '"Tran, Benoit"'
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 optimization problems.
Externí odkaz:
http://arxiv.org/abs/2410.11066
Autor:
Qu, Zheng, Tran, Benoît
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 Distance, which is a distance between scenario trees (or discrete time stoch
Externí odkaz:
http://arxiv.org/abs/2107.09864
Interchange theorems between minimization and integration are useful in optimization, especially in optimal control and in stochastic optimization. In this article, we establish a generalized minimization interchange theorem, where integration is rep
Externí odkaz:
http://arxiv.org/abs/2107.05903
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 Programming (MSP), with independent noises of finite supports. To tackl
Externí odkaz:
http://arxiv.org/abs/2010.10619
Several attempts to dampen the curse of dimensionnality problem of the Dynamic Programming approach for solving multistage optimization problems have been investigated. One popular way to address this issue is the Stochastic Dual Dynamic Programming
Externí odkaz:
http://arxiv.org/abs/1810.12870
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