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Stochastic dual dynamic programming with stagewise dependent objective uncertainty

Anthony Downward (a.downward***at***auckland.ac.nz)
Oscar Dowson (o.dowson***at***auckland.ac.nz)
Regan Baucke (r.baucke***at***auckland.ac.nz)

Abstract: We present a new algorithm for solving linear multistage stochastic programming problems with objective function coefficients modeled as a stochastic process. This algorithm overcomes the difficulties of existing methods which require discretization. Using an argument based on the finiteness of the set of possible cuts, we prove that the algorithm converges almost surely. Finally, we demonstrate the practical application of the algorithm on a hydro-bidding example with the spot-price modeled as an auto-regressive process.

Keywords: dynamic programming, decomposition, multistage, SDDP, stochastic programming

Category 1: Stochastic Programming

Citation: University of Auckland, Level 3, 70 Symonds Street, Auckland, New Zealand. February/2018

Download: [PDF]

Entry Submitted: 02/04/2018
Entry Accepted: 02/05/2018
Entry Last Modified: 07/10/2018

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