Abstract
We focus on the discretization approach to distributionally robust optimization (DRO) problems and propose a numerical scheme originated from the primal–dual hybrid gradient (PDHG) method that recently has been well studied in convex optimization area. Specifically, we consider the cases where the ambiguity set of the discretized DRO model is defined through the moment condition and Wasserstein metric, respectively. Moreover, we apply the PDHG to a portfolio selection problem modelled by DRO and verify its efficiency.
Original language | English |
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Pages (from-to) | 625-630 |
Number of pages | 6 |
Journal | Operations Research Letters |
Volume | 45 |
Issue number | 6 |
DOIs | |
Publication status | Published - Nov 2017 |
User-Defined Keywords
- Discretization method
- Distributionally robust optimization
- Moment conditions
- Primal–dual hybrid gradient
- Wasserstein metric