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This work was completed during my tenure as a scientific assistant and d- toral student at the Insti...
In this paper we extend directly adaptive multicut aggregation method of Svyatoslav Trukhanov, Lewis...
Stochastic programming is a mathematical optimization model for decision making when the uncertainty...
International audienceWe prove the almost-sure convergence of a class of sampling-based nested decom...
A general decomposition framework for large convex optimization problems based on augmented Lagrangi...
This paper derives a new splitting-based decomposition algorithm for convex stochastic programs. It ...
A general decomposition framework for large convex optimization problems based on augmented Lagrangi...
A general decomposition framework for large convex optimization problems based on augmented Lagrangi...
The paper presents a convergence proof for a broad class of sampling algorithms for multistage stoch...
Stochastic programming problems have very large dimension and characteristic structures which are tr...
2016-06-16Stochastic Programming (SP) has long been considered as a well-justified yet computational...
This paper presents a new and high performance solution method for multistage stochastic convex prog...
This book investigates convex multistage stochastic programs whose objective and constraint function...
Zhao [28] recently showed that the log barrier associated with the recourse function of two-stage st...
This paper considers large-scale multistage stochastic linear programs. Sampling is incorporated int...
This work was completed during my tenure as a scientific assistant and d- toral student at the Insti...
In this paper we extend directly adaptive multicut aggregation method of Svyatoslav Trukhanov, Lewis...
Stochastic programming is a mathematical optimization model for decision making when the uncertainty...
International audienceWe prove the almost-sure convergence of a class of sampling-based nested decom...
A general decomposition framework for large convex optimization problems based on augmented Lagrangi...
This paper derives a new splitting-based decomposition algorithm for convex stochastic programs. It ...
A general decomposition framework for large convex optimization problems based on augmented Lagrangi...
A general decomposition framework for large convex optimization problems based on augmented Lagrangi...
The paper presents a convergence proof for a broad class of sampling algorithms for multistage stoch...
Stochastic programming problems have very large dimension and characteristic structures which are tr...
2016-06-16Stochastic Programming (SP) has long been considered as a well-justified yet computational...
This paper presents a new and high performance solution method for multistage stochastic convex prog...
This book investigates convex multistage stochastic programs whose objective and constraint function...
Zhao [28] recently showed that the log barrier associated with the recourse function of two-stage st...
This paper considers large-scale multistage stochastic linear programs. Sampling is incorporated int...
This work was completed during my tenure as a scientific assistant and d- toral student at the Insti...
In this paper we extend directly adaptive multicut aggregation method of Svyatoslav Trukhanov, Lewis...
Stochastic programming is a mathematical optimization model for decision making when the uncertainty...