Abstract
Stochastic multistage decision problems appear in many - if not all - application areas of Operations Research. While to define such problems is easy, to solve them is quite difficult, since they are of infinite dimension. Numerical solution can only be found by solving an approximate, easier problem. In this paper, we show good approximations can be found, where we emphasize the recursive structure of the involved algorithms and data structures. In a second part, the problem of coping with the model error of approximations is discussed. We present algorithms for finding distributionally robust solutions for the model error problem. We also review some application cases of such situations from the literature.
Titel in Übersetzung | Mehrstufige stochastische Optimierung: Approximation durch rekursive Strukturen und Ambiguity Modellierung |
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Originalsprache | Englisch |
Seiten (von - bis) | 1027-1039 |
Seitenumfang | 13 |
Fachzeitschrift | European Journal of Operational Research |
Jahrgang | 306 |
Ausgabenummer | 3 |
Frühes Online-Datum | 8 Apr. 2022 |
DOIs | |
Publikationsstatus | Veröffentlicht - 1 Mai 2023 |
ÖFOS 2012
- 101016 Optimierung
- 101015 Operations Research
- 101019 Stochastik