IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v277y2019i3p953-963.html
   My bibliography  Save this article

K-adaptability in stochastic combinatorial optimization under objective uncertainty

Author

Listed:
  • Buchheim, Christoph
  • Pruente, Jonas

Abstract

We address combinatorial optimization problems with uncertain objective functions, given by discrete probability distributions. Within this setting, we investigate the so-called K-adaptability approach: the aim is to calculate a set of K feasible solutions such that the objective value of the best of these solutions, calculated in each scenario independently, is optimal in expectation. Interpreted as a stochastic optimization problem, we only consider second-stage variables, however, the corresponding candidate solutions are selected in the first stage, i.e., before the scenario is known.

Suggested Citation

  • Buchheim, Christoph & Pruente, Jonas, 2019. "K-adaptability in stochastic combinatorial optimization under objective uncertainty," European Journal of Operational Research, Elsevier, vol. 277(3), pages 953-963.
    • Handle: RePEc:eee:ejores:v:277:y:2019:i:3:p:953-963
    DOI: 10.1016/j.ejor.2019.03.045
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221719303030
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2019.03.045?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    2. Grani A. Hanasusanto & Daniel Kuhn & Wolfram Wiesemann, 2015. "K -Adaptability in Two-Stage Robust Binary Programming," Operations Research, INFORMS, vol. 63(4), pages 877-891, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Goerigk, Marc & Hartisch, Michael, 2023. "A framework for inherently interpretable optimization models," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1312-1324.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Detienne, Boris & Lefebvre, Henri & Malaguti, Enrico & Monaci, Michele, 2024. "Adjustable robust optimization with objective uncertainty," European Journal of Operational Research, Elsevier, vol. 312(1), pages 373-384.
    2. Feng, Wei & Feng, Yiping & Zhang, Qi, 2021. "Multistage robust mixed-integer optimization under endogenous uncertainty," European Journal of Operational Research, Elsevier, vol. 294(2), pages 460-475.
    3. Portoleau, Tom & Artigues, Christian & Guillaume, Romain, 2024. "Robust decision trees for the multi-mode project scheduling problem with a resource investment objective and uncertain activity duration," European Journal of Operational Research, Elsevier, vol. 312(2), pages 525-540.
    4. Rodrigues, Filipe & Agra, Agostinho, 2021. "An exact robust approach for the integrated berth allocation and quay crane scheduling problem under uncertain arrival times," European Journal of Operational Research, Elsevier, vol. 295(2), pages 499-516.
    5. Jannis Kurtz, 2018. "Robust combinatorial optimization under budgeted–ellipsoidal uncertainty," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(4), pages 315-337, December.
    6. Anirudh Subramanyam & Frank Mufalli & José M. Lí?nez-Aguirre & Jose M. Pinto & Chrysanthos E. Gounaris, 2021. "Robust Multiperiod Vehicle Routing Under Customer Order Uncertainty," Operations Research, INFORMS, vol. 69(1), pages 30-60, January.
    7. Marc Goerigk & Adam Kasperski & Paweł Zieliński, 2022. "Robust two-stage combinatorial optimization problems under convex second-stage cost uncertainty," Journal of Combinatorial Optimization, Springer, vol. 43(3), pages 497-527, April.
    8. Cohen, Izack & Postek, Krzysztof & Shtern, Shimrit, 2023. "An adaptive robust optimization model for parallel machine scheduling," European Journal of Operational Research, Elsevier, vol. 306(1), pages 83-104.
    9. Aakil M. Caunhye & Nazli Yonca Aydin & H. Sebnem Duzgun, 2020. "Robust post-disaster route restoration," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 1055-1087, December.
    10. Omar El Housni & Vineet Goyal, 2021. "On the Optimality of Affine Policies for Budgeted Uncertainty Sets," Mathematics of Operations Research, INFORMS, vol. 46(2), pages 674-711, May.
    11. Bakker, Hannah & Dunke, Fabian & Nickel, Stefan, 2020. "A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice," Omega, Elsevier, vol. 96(C).
    12. Dimitrios Letsios & Jeremy T. Bradley & Suraj G & Ruth Misener & Natasha Page, 2021. "Approximate and robust bounded job start scheduling for Royal Mail delivery offices," Journal of Scheduling, Springer, vol. 24(2), pages 237-258, April.
    13. Bertsimas, Dimitris & Ng, Yeesian, 2019. "Robust and stochastic formulations for ambulance deployment and dispatch," European Journal of Operational Research, Elsevier, vol. 279(2), pages 557-571.
    14. 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.
    15. Jonathan De La Vega & Pedro Munari & Reinaldo Morabito, 2019. "Robust optimization for the vehicle routing problem with multiple deliverymen," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(4), pages 905-936, December.
    16. Letsios, Dimitrios & Mistry, Miten & Misener, Ruth, 2021. "Exact lexicographic scheduling and approximate rescheduling," European Journal of Operational Research, Elsevier, vol. 290(2), pages 469-478.
    17. Wang, Xinfang (Jocelyn) & Paul, Jomon A., 2020. "Robust optimization for hurricane preparedness," International Journal of Production Economics, Elsevier, vol. 221(C).
    18. Hossein Hashemi Doulabi & Patrick Jaillet & Gilles Pesant & Louis-Martin Rousseau, 2021. "Exploiting the Structure of Two-Stage Robust Optimization Models with Exponential Scenarios," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 143-162, January.
    19. François Clautiaux & Boris Detienne & Henri Lefebvre, 2023. "A two-stage robust approach for minimizing the weighted number of tardy jobs with objective uncertainty," Journal of Scheduling, Springer, vol. 26(2), pages 169-191, April.
    20. Jianwen Ren & Yingqiang Xu & Shiyuan Wang, 2018. "A Distributed Robust Dispatch Approach for Interconnected Systems with a High Proportion of Wind Power Penetration," Energies, MDPI, vol. 11(4), pages 1-18, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:277:y:2019:i:3:p:953-963. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.