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From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization

Author

Listed:
  • Wenqing Chen

    (NUS Business School, National University of Singapore, Singapore)

  • Melvyn Sim

    (NUS Business School and NUS Risk Management Institute, National University of Singapore, Singapore)

  • Jie Sun

    (NUS Business School and NUS Risk Management Institute, National University of Singapore, Singapore)

  • Chung-Piaw Teo

    (NUS Business School, National University of Singapore, Singapore)

Abstract

We review and develop different tractable approximations to individual chance-constrained problems in robust optimization on a variety of uncertainty sets and show their interesting connections with bounds on the conditional-value-at-risk (CVaR) measure. We extend the idea to joint chance-constrained problems and provide a new formulation that improves upon the standard approach. Our approach builds on a classical worst-case bound for order statistics problems and is applicable even if the constraints are correlated. We provide an application of the model on a network resource allocation problem with uncertain demand.

Suggested Citation

  • Wenqing Chen & Melvyn Sim & Jie Sun & Chung-Piaw Teo, 2010. "From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization," Operations Research, INFORMS, vol. 58(2), pages 470-485, April.
    • Handle: RePEc:inm:oropre:v:58:y:2010:i:2:p:470-485
    DOI: 10.1287/opre.1090.0712
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    References listed on IDEAS

    as
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