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On 2-stage robust LP with RHS uncertainty: complexity results and applications

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  • Michel Minoux

Abstract

We investigate here the class—denoted R-LP-RHSU—of two-stage robust linear programming problems with right-hand-side uncertainty. Such problems arise in many applications e.g: robust PERT scheduling (with uncertain task durations); robust maximum flow (with uncertain arc capacities); robust network capacity expansion problems; robust inventory management; some robust production planning problems in the context of power production/distribution systems. It is shown that such problems can be formulated as large scale linear programs with associated nonconvex separation subproblem. A formal proof of strong NP-hardness for the general case is then provided, and polynomially solvable subclasses are exhibited. Differences with other previously described robust LP problems (featuring row-wise uncertainty instead of column wise uncertainty) are highlighted. Copyright Springer Science+Business Media, LLC. 2011

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  • Michel Minoux, 2011. "On 2-stage robust LP with RHS uncertainty: complexity results and applications," Journal of Global Optimization, Springer, vol. 49(3), pages 521-537, March.
  • Handle: RePEc:spr:jglopt:v:49:y:2011:i:3:p:521-537
    DOI: 10.1007/s10898-010-9645-2
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    Cited by:

    1. Philippe Chrétienne, 2021. "Reactive and proactive single-machine scheduling to maintain a maximum number of starting times," Annals of Operations Research, Springer, vol. 298(1), pages 111-124, March.
    2. 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.
    3. Krumke, Sven O. & Schmidt, Eva & Streicher, Manuel, 2019. "Robust multicovers with budgeted uncertainty," European Journal of Operational Research, Elsevier, vol. 274(3), pages 845-857.
    4. Christoph Buchheim & Jannis Kurtz, 2018. "Robust combinatorial optimization under convex and discrete cost uncertainty," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 211-238, September.
    5. Bruni, M.E. & Di Puglia Pugliese, L. & Beraldi, P. & Guerriero, F., 2017. "An adjustable robust optimization model for the resource-constrained project scheduling problem with uncertain activity durations," Omega, Elsevier, vol. 71(C), pages 66-84.
    6. Mattia, Sara & Rossi, Fabrizio & Servilio, Mara & Smriglio, Stefano, 2017. "Staffing and scheduling flexible call centers by two-stage robust optimization," Omega, Elsevier, vol. 72(C), pages 25-37.
    7. Nicolas Kämmerling & Jannis Kurtz, 2020. "Oracle-based algorithms for binary two-stage robust optimization," Computational Optimization and Applications, Springer, vol. 77(2), pages 539-569, November.
    8. Idir Hamaz & Laurent Houssin & Sonia Cafieri, 2018. "A robust basic cyclic scheduling problem," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 291-313, September.
    9. Mehdi Karimi & Somayeh Moazeni & Levent Tunçel, 2018. "A Utility Theory Based Interactive Approach to Robustness in Linear Optimization," Journal of Global Optimization, Springer, vol. 70(4), pages 811-842, April.
    10. Andreas Thorsen & Tao Yao, 2017. "Robust inventory control under demand and lead time uncertainty," Annals of Operations Research, Springer, vol. 257(1), pages 207-236, October.
    11. Dimitris Bertsimas & Frans J. C. T. de Ruiter, 2016. "Duality in Two-Stage Adaptive Linear Optimization: Faster Computation and Stronger Bounds," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 500-511, August.

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