On Robust Dynamic Programming

Robust Dual Dynamic Programming

Multi-stage robust optimization problems, where the decision maker can dynamically react to consecutively observed realizations of the uncertain problem parameters, pose formidable theoretical and computational challenges. As a result, the existing solution approaches for this problem class typically determine suboptimal solutions under restrictive assumptions. In this paper, we propose a robus...

Robust dynamic programming via multi-parametric programming

In this work, we present a new algorithm for solving complex multi-stage optimisation problems involving hard constraints and uncertainties, based on dynamic and multi-parametric programming. Each echelon of the dynamic programming procedure, typically employed in the context of multi-stage optimisation models, is interpreted as a robust multi-parametric optimisation problem, with the present s...

Robust Parsing Using Dynamic Programming

Robust Data-Driven Dynamic Programming

In stochastic optimal control the distribution of the exogenous noise is typically unknown and must be inferred from limited data before dynamic programming (DP)-based solution schemes can be applied. If the conditional expectations in the DP recursions are estimated via kernel regression, however, the historical sample paths enter the solution procedure directly as they determine the evaluatio...

Robust Process Control by Dynamic Stochastic Programming

Unnecessarily conservative behavior of standard process control techniques can be avoided by stochastic programming models when the distribution of random distur­ bances is known. In an earlier study we have investigated such an approach for tank level constraints of a distillation process. Here we address techniques that have accelerated the numerical solution of the large and expensive stocha...