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Robust approaches for optimization problems with convex uncertainty

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  • Roos, Ernst

    (Tilburg University, School of Economics and Management)

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  • Roos, Ernst, 2021. "Robust approaches for optimization problems with convex uncertainty," Other publications TiSEM dd9e7b35-a770-4f8d-a85c-8, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:dd9e7b35-a770-4f8d-a85c-86c6aef23167
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    References listed on IDEAS

    as
    1. Philip B. Zwart, 1974. "Global Maximization of a Convex Function with Linear Inequality Constraints," Operations Research, INFORMS, vol. 22(3), pages 602-609, June.
    2. Yanıkoğlu, İhsan & Gorissen, Bram L. & den Hertog, Dick, 2019. "A survey of adjustable robust optimization," European Journal of Operational Research, Elsevier, vol. 277(3), pages 799-813.
    3. Zhen, Jianzhe, 2018. "Adjustable robust optimization : Theory, algorithm and applications," Other publications TiSEM d7f25656-92c5-45bf-b103-c, Tilburg University, School of Economics and Management.
    4. Jinfeng Yue & Bintong Chen & Min-Chiang Wang, 2006. "Expected Value of Distribution Information for the Newsvendor Problem," Operations Research, INFORMS, vol. 54(6), pages 1128-1136, December.
    5. Guidong Zhu & Jonathan F. Bard & Gang Yu, 2006. "A Branch-and-Cut Procedure for the Multimode Resource-Constrained Project-Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 18(3), pages 377-390, August.
    6. Huan Xu & Constantine Caramanis & Shie Mannor, 2012. "A Distributional Interpretation of Robust Optimization," Mathematics of Operations Research, INFORMS, vol. 37(1), pages 95-110, February.
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