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Recourse-based stochastic nonlinear programming: properties and Benders-SQP algorithms

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  • Ankur Kulkarni
  • Uday Shanbhag

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  • Ankur Kulkarni & Uday Shanbhag, 2012. "Recourse-based stochastic nonlinear programming: properties and Benders-SQP algorithms," Computational Optimization and Applications, Springer, vol. 51(1), pages 77-123, January.
  • Handle: RePEc:spr:coopap:v:51:y:2012:i:1:p:77-123
    DOI: 10.1007/s10589-010-9316-8
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    References listed on IDEAS

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    1. Stephen M. Robinson, 1996. "Analysis of Sample-Path Optimization," Mathematics of Operations Research, INFORMS, vol. 21(3), pages 513-528, August.
    2. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    3. Jeff Linderoth & Alexander Shapiro & Stephen Wright, 2006. "The empirical behavior of sampling methods for stochastic programming," Annals of Operations Research, Springer, vol. 142(1), pages 215-241, February.
    4. Xiaojun Chen & Masao Fukushima, 2005. "Expected Residual Minimization Method for Stochastic Linear Complementarity Problems," Mathematics of Operations Research, INFORMS, vol. 30(4), pages 1022-1038, November.
    5. Rockafellar, R. T. & Wets, R. J. -B., 1975. "Stochastic convex programming: Kuhn-Tucker conditions," Journal of Mathematical Economics, Elsevier, vol. 2(3), pages 349-370, December.
    6. Arjan Berkelaar & Cees Dert & Bart Oldenkamp & Shuzhong Zhang, 2002. "A Primal-Dual Decomposition-Based Interior Point Approach to Two-Stage Stochastic Linear Programming," Operations Research, INFORMS, vol. 50(5), pages 904-915, October.
    7. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    8. Zhang, S., 2002. "An interior-point and decomposition approach to multiple stage stochastic programming," Econometric Institute Research Papers EI 2002-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Blomvall, Jorgen & Lindberg, Per Olov, 2002. "A Riccati-based primal interior point solver for multistage stochastic programming," European Journal of Operational Research, Elsevier, vol. 143(2), pages 452-461, December.
    10. John R. Birge, 1985. "Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs," Operations Research, INFORMS, vol. 33(5), pages 989-1007, October.
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    Cited by:

    1. Sebastián Arpón & Tito Homem-de-Mello & Bernardo K. Pagnoncelli, 2020. "An ADMM algorithm for two-stage stochastic programming problems," Annals of Operations Research, Springer, vol. 286(1), pages 559-582, March.
    2. Chen, Wenyi & Kucukyazici, Beste & Verter, Vedat & Jesús Sáenz, María, 2015. "Supply chain design for unlocking the value of remanufacturing under uncertainty," European Journal of Operational Research, Elsevier, vol. 247(3), pages 804-819.
    3. Jinlong Lei & Uday V. Shanbhag & Jong-Shi Pang & Suvrajeet Sen, 2020. "On Synchronous, Asynchronous, and Randomized Best-Response Schemes for Stochastic Nash Games," Mathematics of Operations Research, INFORMS, vol. 45(1), pages 157-190, February.

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