# Ambiguous Chance-Constrained Binary Programs under Mean-Covariance Information

@article{Zhang2016AmbiguousCB, title={Ambiguous Chance-Constrained Binary Programs under Mean-Covariance Information}, author={Yiling Zhang and Ruiwei Jiang and Siqian Shen}, journal={SIAM J. Optim.}, year={2016}, volume={28}, pages={2922-2944} }

We consider chance-constrained binary programs, where each row of the inequalities that involve uncertainty needs to be satisfied probabilistically. Only the information of the mean and covariance ...

## 59 Citations

### Strong Formulations for Distributionally Robust Chance-Constrained Programs with Left-Hand Side Uncertainty Under Wasserstein Ambiguity

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- 2022

This work exploits the connection between nominal chance-constrained programs and DR-CCP to obtain strong formulations with significant enhancements, and proposes an exponential class of inequalities that can be separated efficiently within a branch-and-cut framework.

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We study a pessimistic stochastic bilevel program in the context of sequential two-player games, where the leader makes a binary here-and-now decision, and the follower responds a continuous…

### Optimized Bonferroni approximations of distributionally robust joint chance constraints

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This paper shows that an optimized version of Bonferroni approximation of a distributionally robust joint chance constraint is exact when the uncertainties are separable across the individual inequalities, i.e., each uncertain constraint involves a different set of uncertain parameters and corresponding distribution families.

### On distributionally robust chance constrained programs with Wasserstein distance

- Computer ScienceMathematical Programming
- 2019

It is shown that a DRCCP can be reformulated as a conditional value-at-risk constrained optimization problem, and thus admits tight inner and outer approximations and a big-M free formulation.

### Multistage distributionally robust mixed-integer programming with decision-dependent moment-based ambiguity sets

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- Computer Science
- 2021

It is demonstrated that optimal solutions to robust binary knapsack problems with inner and outer polyhedral approximations of the ellipsoidal uncertainty set can provide both upper and lower bounds on the optimal value of the second-order cone-constrained binaryknapsack problem, and it is proved that the solution providing the upper bound converges to the optimal solution.

### Chance-constrained optimization under limited distributional information: A review of reformulations based on sampling and distributional robustness

- Computer ScienceEURO Journal on Computational Optimization
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### Joint chance-constrained programs and the intersection of mixing sets through a submodularity lens

- MathematicsMathematical Programming
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This paper first revisits basic mixing sets by establishing a strong and previously unrecognized connection to submodularity, and shows that mixing inequalities with binary variables are nothing but the polymatroid inequalities associated with a specific submodular function.

### Building Load Control Using Distributionally Robust Chance-Constrained Programs with Right-Hand Side Uncertainty and the Risk-Adjustable Variants

- EngineeringINFORMS J. Comput.
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Aggregation of heating, ventilation, and air conditioning (HVAC) loads can provide reserves to absorb volatile renewable energy, especially solar photo-voltaic (PV) generation. In this paper, we…

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- Computer Science, Economics
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The main tractable reformulations in this paper are projected into the original decision space and thus can be interpreted as conventional two-stage stochastic programs under discrete support with extra penalty terms enforcing the robustness.

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