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A relaxation algorithm with a probabilistic guarantee for robust deviation optimization

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  • Akiko Takeda
  • Shunsuke Taguchi
  • Tsutomu Tanaka

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  • Akiko Takeda & Shunsuke Taguchi & Tsutomu Tanaka, 2010. "A relaxation algorithm with a probabilistic guarantee for robust deviation optimization," Computational Optimization and Applications, Springer, vol. 47(1), pages 1-31, September.
    • Handle: RePEc:spr:coopap:v:47:y:2010:i:1:p:1-31
    DOI: 10.1007/s10589-008-9212-7
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    References listed on IDEAS

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    1. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
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    Cited by:

    1. Takafumi Kanamori & Akiko Takeda, 2012. "Worst-Case Violation of Sampled Convex Programs for Optimization with Uncertainty," Journal of Optimization Theory and Applications, Springer, vol. 152(1), pages 171-197, January.
    2. Chassein, André & Goerigk, Marc, 2017. "Minmax regret combinatorial optimization problems with ellipsoidal uncertainty sets," European Journal of Operational Research, Elsevier, vol. 258(1), pages 58-69.
    3. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    4. Raphael Hauser & Vijay Krishnamurthy & Reha Tutuncu, 2013. "Relative Robust Portfolio Optimization," Papers 1305.0144, arXiv.org, revised May 2013.
    5. Groetzner, Patrick & Werner, Ralf, 2022. "Multiobjective optimization under uncertainty: A multiobjective robust (relative) regret approach," European Journal of Operational Research, Elsevier, vol. 296(1), pages 101-115.

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