stochastic dual dynamic programming algorithm

On the convergence of decomposition methods for multi-stage stochastic convex programs

Published: 2012/04/24, Updated: 2013/05/25

Convex Optimization, Dynamic Programming, Stochastic Programming benders decomposition, dynamic programming, monte carlo sampling, stochastic dual dynamic programming algorithm, stochastic programming

We prove the almost-sure convergence of a class of sampling-based nested decomposition algorithms for multistage stochastic convex programs in which the stage costs are general convex functions of the decisions, and uncertainty is modelled by a scenario tree. As special cases, our results imply the almost-sure convergence of SDDP, CUPPS and DOASA when applied to … Read more

Analysis of Stochastic Dual Dynamic Programming Method

Published: 2009/12/30, Updated: 2010/05/29

Alexander Shapiro

Stochastic Programming monte carlo sampling, risk averse optimization, sample average approximation method, stochastic dual dynamic programming algorithm, stochastic programming

In this paper we discuss statistical properties and rates of convergence of the Stochastic Dual Dynamic Programming (SDDP) method applied to multistage linear stochastic programming problems. We assume that the underline data process is stagewise independent and consider the framework where at first a random sample from the original (true) distribution is generated and consequently … Read more