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α-Conservative approximation for probabilistically constrained convex programs

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  • Yuichi Takano
  • Jun-ya Gotoh

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  • Yuichi Takano & Jun-ya Gotoh, 2010. "α-Conservative approximation for probabilistically constrained convex programs," Computational Optimization and Applications, Springer, vol. 46(1), pages 113-133, May.
    • Handle: RePEc:spr:coopap:v:46:y:2010:i:1:p:113-133
    DOI: 10.1007/s10589-008-9178-5
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    References listed on IDEAS

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    1. Bruce L. Miller & Harvey M. Wagner, 1965. "Chance Constrained Programming with Joint Constraints," Operations Research, INFORMS, vol. 13(6), pages 930-945, December.
    2. Laurent El Ghaoui & Maksim Oks & Francois Oustry, 2003. "Worst-Case Value-At-Risk and Robust Portfolio Optimization: A Conic Programming Approach," Operations Research, INFORMS, vol. 51(4), pages 543-556, August.
    3. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    4. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
    5. A. Charnes & W. W. Cooper & G. H. Symonds, 1958. "Cost Horizons and Certainty Equivalents: An Approach to Stochastic Programming of Heating Oil," Management Science, INFORMS, vol. 4(3), pages 235-263, April.
    6. M. Gilli & E. Kellezi & H. Hysi, 2006. "A Data-Driven Optimization Heuristic for Downside Risk Minimization," Computing in Economics and Finance 2006 355, Society for Computational Economics.
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