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Frameworks and results in distributionally robust optimization
The concepts of risk aversion, chance-constrained optimization, and robust optimization
have developed significantly over the last decade. The statistical learning community has …
have developed significantly over the last decade. The statistical learning community has …
[HTML][HTML] Distributionally robust optimization: A review on theory and applications
In this paper, we survey the primary research on the theory and applications of
distributionally robust optimization (DRO). We start with reviewing the modeling power and …
distributionally robust optimization (DRO). We start with reviewing the modeling power and …
Data-driven stochastic programming using phi-divergences
Most of classical stochastic programming assumes that the distribution of uncertain
parameters are known, and this distribution is an input to the model. In many applications …
parameters are known, and this distribution is an input to the model. In many applications …
Multistage distributionally robust mixed-integer programming with decision-dependent moment-based ambiguity sets
We study multistage distributionally robust mixed-integer programs under endogenous
uncertainty, where the probability distribution of stage-wise uncertainty depends on the …
uncertainty, where the probability distribution of stage-wise uncertainty depends on the …
Distributionally robust optimization with decision dependent ambiguity sets
We study decision dependent distributionally robust optimization models, where the
ambiguity sets of probability distributions can depend on the decision variables. These …
ambiguity sets of probability distributions can depend on the decision variables. These …
Data-driven chance constrained optimization under Wasserstein ambiguity sets
We present a data-driven approach for distri-butionally robust chance constrained
optimization problems (DRCCPs). We consider the case where the decision maker has …
optimization problems (DRCCPs). We consider the case where the decision maker has …
Security-constrained optimal sizing and siting of BESS in hybrid AC/DC microgrid considering post-contingency corrective rescheduling
Hybrid AC/DC microgrids allow the integration of diverse renewable energy resources.
However, the security and the reliability of hybrid AC/DC microgrid systems are challenged …
However, the security and the reliability of hybrid AC/DC microgrid systems are challenged …
Decomposition algorithm for distributionally robust optimization using Wasserstein metric with an application to a class of regression models
We study distributionally robust optimization (DRO) problems where the ambiguity set is
defined using the Wasserstein metric and can account for a bounded support. We show that …
defined using the Wasserstein metric and can account for a bounded support. We show that …
Distributionally robust portfolio optimization with second-order stochastic dominance based on wasserstein metric
In portfolio optimization, we may be dealing with misspecification of a known distribution,
that stock returns follow it. The unknown true distribution is considered in terms of a …
that stock returns follow it. The unknown true distribution is considered in terms of a …
Distributionally robust optimization with matrix moment constraints: Lagrange duality and cutting plane methods
A key step in solving minimax distributionally robust optimization (DRO) problems is to
reformulate the inner maximization wrt probability measure as a semiinfinite programming …
reformulate the inner maximization wrt probability measure as a semiinfinite programming …