2071. Pareto front for two-stage distributionally robust optimization problems
Invited abstract in session TB-31: Robust and Distributionally Robust Optimization - Theory and Applications, stream Stochastic and Robust optimization.
Tuesday, 10:30-12:00Room: Maurice Keyworth 1.06
Authors (first author is the speaker)
| 1. | Filipe Rodrigues
|
| ISEG, University of Lisbon | |
| 2. | Agostinho Agra
|
| Matemática, Universidade de Aveiro |
Abstract
Two-stage distributionally robust optimization (DRO) is a powerful optimization technique to handle uncertainty that is less conservative than robust optimization and more flexible than stochastic programming. The probability distribution of the uncertain parameters is not known but assumed to belong to an ambiguity set. The size of certain types of ambiguity sets - such as several discrepancy-based ambiguity sets - is defined by a single parameter that makes it possible to control the degree of conservatism of the underlying optimization problem. Finding the values to assign to this parameter is a very relevant research topic. In this presentation, we propose an exact and several heuristic methods for determining control parameter values leading to all the relevant first-stage solutions of a DRO model. The applicability of the proposed methods is shown on instances of the scheduling problem.
Keywords
- Robust Optimization
- Programming, Stochastic
- Scheduling
Status: accepted
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