WIAS Preprint No. 2271, (2016)

Joint dynamic probabilistic constraints with projected linear decision rules



Authors

  • Guigues, Vincent
  • Henrion, René

2010 Mathematics Subject Classification

  • 90C15 90C90 90C30

Keywords

  • dynamic probabilistic constraints, multistage stochastic linear programs, linear decision rules

Abstract

We consider multistage stochastic linear optimization problems combining joint dynamic probabilistic constraints with hard constraints. We develop a method for projecting decision rules onto hard constraints of wait-and-see type. We establish the relation between the original (infinite dimensional) problem and approximating problems working with projections from different subclasses of decision policies. Considering the subclass of linear decision rules and a generalized linear model for the underlying stochastic process with noises that are Gaussian or truncated Gaussian, we show that the value and gradient of the objective and constraint functions of the approximating problems can be computed analytically.

Appeared in

  • Optim. Methods Softw., 32 (2017) pp. 1006--1032.

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