Optimization problems arising in practice usually contain several random parameters. Hence, in order to obtain optimal solutions being robust with respect to random parameter variations, the mostly available statistical information about the random parameters should be considered already at the...

1. Optimal Control under Stochastic Uncertainty -- 2. Stochastic Optimization of Regulators -- 3. Optimal Open-Loop Control of Dynamic Systems under Stochastic Uncertainty -- 4. Construction of feedback control by means of homotopy methods -- 5. Constructions of Limit State Functions -- 6....

Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data,...

I. Dynamic Decision Problems under Uncertainty: Modeling Aspects -- Reflections on Output Analysis for Multistage Stochastic Linear Programs -- Modeling Support for Multistage Recourse Problems -- Optimal Solutions for Undiscounted Variance Penalized Markov Decision Chains -- Approximation and...