Conic reformulations for Kullback-Leibler divergence constrained distributionally robust optimization and applications
In this paper, we consider a Kullback-Leibler divergence constrained distributionally robust optimization model. This model considers an ambiguity set that consists of all distributions whose Kullback-Leibler divergence to an empirical distribution is bounded. Utilizing the fact that this divergenc...
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| Format: | Article |
| Language: | English |
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Balikesir University
2021-04-01
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| Series: | An International Journal of Optimization and Control: Theories & Applications |
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| Online Access: | http://www.ijocta.org/index.php/files/article/view/1001 |