IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v168y2006i3p967-984.html
   My bibliography  Save this article

Cutting plane method for multiple objective stochastic integer linear programming

Author

Listed:
  • Abbas, Moncef
  • Bellahcene, Fatima

Abstract

No abstract is available for this item.

Suggested Citation

  • Abbas, Moncef & Bellahcene, Fatima, 2006. "Cutting plane method for multiple objective stochastic integer linear programming," European Journal of Operational Research, Elsevier, vol. 168(3), pages 967-984, February.
  • Handle: RePEc:eee:ejores:v:168:y:2006:i:3:p:967-984
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(04)00343-1
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Teghem, J. & Dufrane, D. & Thauvoye, M. & Kunsch, P., 1986. "Strange: An interactive method for multi-objective linear programming under uncertainty," European Journal of Operational Research, Elsevier, vol. 26(1), pages 65-82, July.
    2. Klein, Dieter & Hannan, Edward, 1982. "An algorithm for the multiple objective integer linear programming problem," European Journal of Operational Research, Elsevier, vol. 9(4), pages 378-385, April.
    3. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    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. Chaabane Djamal & Mebrek Fatma, 2014. "Optimization of a linear function over the set of stochastic efficient solutions," Computational Management Science, Springer, vol. 11(1), pages 157-178, January.
    2. Charles, V. & Udhayakumar, A. & Rhymend Uthariaraj, V., 2010. "An approach to find redundant objective function(s) and redundant constraint(s) in multi-objective nonlinear stochastic fractional programming problems," European Journal of Operational Research, Elsevier, vol. 201(2), pages 390-398, March.
    3. Fatima Bellahcene, 2019. "Decision maker's preferences modeling for multiple objective stochastic linear programming problems," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 29(3), pages 5-16.
    4. Walter J. Gutjahr & Alois Pichler, 2016. "Stochastic multi-objective optimization: a survey on non-scalarizing methods," Annals of Operations Research, Springer, vol. 236(2), pages 475-499, January.
    5. Fatima Bellahcene & Philippe Marthon, 2021. "A compromise solution method for the multiobjective minimum risk problem," Operational Research, Springer, vol. 21(3), pages 1913-1926, September.
    6. Walter Gutjahr & Alois Pichler, 2016. "Stochastic multi-objective optimization: a survey on non-scalarizing methods," Annals of Operations Research, Springer, vol. 236(2), pages 475-499, January.

    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. Sakawa, Masatoshi & Kato, Kosuke & Nishizaki, Ichiro, 2003. "An interactive fuzzy satisficing method for multiobjective stochastic linear programming problems through an expectation model," European Journal of Operational Research, Elsevier, vol. 145(3), pages 665-672, March.
    2. Thomas L. Magnanti, 2021. "Optimization: From Its Inception," Management Science, INFORMS, vol. 67(9), pages 5349-5363, September.
    3. Michael Freimer & Jeffrey Linderoth & Douglas Thomas, 2012. "The impact of sampling methods on bias and variance in stochastic linear programs," Computational Optimization and Applications, Springer, vol. 51(1), pages 51-75, January.
    4. Alonso-Ayuso, Antonio & Escudero, Laureano F. & Teresa Ortuno, M., 2003. "BFC, A branch-and-fix coordination algorithmic framework for solving some types of stochastic pure and mixed 0-1 programs," European Journal of Operational Research, Elsevier, vol. 151(3), pages 503-519, December.
    5. Ringuest, Jeffrey L. & Graves, Samuel B., 2000. "A sampling-based method for generating nondominated solutions in stochastic MOMP problems," European Journal of Operational Research, Elsevier, vol. 126(3), pages 651-661, November.
    6. Hesam Ahmadi & Uday V. Shanbhag, 2020. "On the resolution of misspecified convex optimization and monotone variational inequality problems," Computational Optimization and Applications, Springer, vol. 77(1), pages 125-161, September.
    7. Aghayi, Nazila & Maleki, Bentolhoda, 2016. "Efficiency measurement of DMUs with undesirable outputs under uncertainty based on the directional distance function: Application on bank industry," Energy, Elsevier, vol. 112(C), pages 376-387.
    8. Chen, Chien-Wei & Fan, Yueyue, 2012. "Bioethanol supply chain system planning under supply and demand uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 150-164.
    9. J. F. F. Almeida & S. V. Conceição & L. R. Pinto & B. R. P. Oliveira & L. F. Rodrigues, 2022. "Optimal sales and operations planning for integrated steel industries," Annals of Operations Research, Springer, vol. 315(2), pages 773-790, August.
    10. Nathan Adelgren & Akshay Gupte, 2022. "Branch-and-Bound for Biobjective Mixed-Integer Linear Programming," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 909-933, March.
    11. Escudero, Laureano F. & Quintana, Francisco J. & Salmeron, Javier, 1999. "CORO, a modeling and an algorithmic framework for oil supply, transformation and distribution optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 114(3), pages 638-656, May.
    12. Angelo Aliano Filho & Antonio Carlos Moretti & Margarida Vaz Pato & Washington Alves Oliveira, 2021. "An exact scalarization method with multiple reference points for bi-objective integer linear optimization problems," Annals of Operations Research, Springer, vol. 296(1), pages 35-69, January.
    13. Dönmez, Kadir & Çetek, Cem & Kaya, Onur, 2022. "Air traffic management in parallel-point merge systems under wind uncertainties," Journal of Air Transport Management, Elsevier, vol. 104(C).
    14. Chardy, Matthieu & Klopfenstein, Olivier, 2012. "Handling uncertainties in vehicle routing problems through data preprocessing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 667-683.
    15. Schwarz, Hannes & Kotthoff, Lars & Hoos, Holger & Fichtner, Wolf & Bertsch, Valentin, 2017. "Using automated algorithm configuration to improve the optimization of decentralized energy systems modeled as large-scale, two-stage stochastic programs," Working Paper Series in Production and Energy 24, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    16. Urli, Bruno & Nadeau, Raymond, 2004. "PROMISE/scenarios: An interactive method for multiobjective stochastic linear programming under partial uncertainty," European Journal of Operational Research, Elsevier, vol. 155(2), pages 361-372, June.
    17. Kanudia, Amit & Shukla, PR, 1998. "Modelling of Uncertainties and Price Elastic Demands in Energy-environment Planning for India," Omega, Elsevier, vol. 26(3), pages 409-423, June.
    18. Satya Tamby & Daniel Vanderpooten, 2021. "Enumeration of the Nondominated Set of Multiobjective Discrete Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 72-85, January.
    19. Dehghani, Maryam & Abbasi, Babak & Oliveira, Fabricio, 2021. "Proactive transshipment in the blood supply chain: A stochastic programming approach," Omega, Elsevier, vol. 98(C).
    20. Arie M. C. A. Koster & Michael Poss, 2018. "Special issue on: robust combinatorial optimization," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 207-209, September.

    More about this item

    Statistics

    Access and download statistics

    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:168:y:2006:i:3:p:967-984. 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.