IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v57y2009i1p187-199.html
   My bibliography  Save this article

Generating a Representative Subset of the Nondominated Frontier in Multiple Criteria Decision Making

Author

Listed:
  • Esra Karasakal

    (Department of Industrial Engineering, Middle East Technical University, Ankara 06531, Turkey)

  • Murat Köksalan

    (Department of Industrial Engineering, Middle East Technical University, Ankara 06531, Turkey)

Abstract

In this paper, we address the problem of generating a discrete representation of the nondominated frontier in multiple objective linear problems. We find a surface that approximates the shape of the nondominated frontier. Utilizing the surface, we generate a set of discrete points that is representative of the frontier. Our experience on randomly generated problems demonstrates that the approach performs well in terms of both the quality of the representation and the computation time.

Suggested Citation

  • Esra Karasakal & Murat Köksalan, 2009. "Generating a Representative Subset of the Nondominated Frontier in Multiple Criteria Decision Making," Operations Research, INFORMS, vol. 57(1), pages 187-199, February.
  • Handle: RePEc:inm:oropre:v:57:y:2009:i:1:p:187-199
    DOI: 10.1287/opre.1080.0581
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.1080.0581
    Download Restriction: no

    File URL: https://libkey.io/10.1287/opre.1080.0581?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
    ---><---

    References listed on IDEAS

    as
    1. M. Murat Köksalan & Paul N. S. Sagala, 1995. "Interactive Approaches for Discrete Alternative Multiple Criteria Decision Making with Monotone Utility Functions," Management Science, INFORMS, vol. 41(7), pages 1158-1171, July.
    2. Serpil Sayin, 2003. "A Procedure to Find Discrete Representations of the Efficient Set with Specified Coverage Errors," Operations Research, INFORMS, vol. 51(3), pages 427-436, June.
    3. Pekka Korhonen & Jyrki Wallenius, 1988. "A pareto race," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(6), pages 615-623, December.
    4. S. Ruzika & M. M. Wiecek, 2005. "Approximation Methods in Multiobjective Programming," Journal of Optimization Theory and Applications, Springer, vol. 126(3), pages 473-501, September.
    5. Yan Fu & Urmila Diwekar, 2004. "An Efficient Sampling Approach to Multiobjective Optimization," Annals of Operations Research, Springer, vol. 132(1), pages 109-134, November.
    6. M. Murat Köksalan, 1999. "A heuristic approach to bicriteria scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(7), pages 777-789, October.
    7. Dauer, Jerald P. & Gallagher, Richard J., 1996. "A combined constraint-space, objective-space approach for determining high-dimensional maximal efficient faces of multiple objective linear programs," European Journal of Operational Research, Elsevier, vol. 88(2), pages 368-381, January.
    8. H. P. Benson, 1998. "Hybrid Approach for Solving Multiple-Objective Linear Programs in Outcome Space," Journal of Optimization Theory and Applications, Springer, vol. 98(1), pages 17-35, July.
    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. Ceyhan, Gökhan & Köksalan, Murat & Lokman, Banu, 2019. "Finding a representative nondominated set for multi-objective mixed integer programs," European Journal of Operational Research, Elsevier, vol. 272(1), pages 61-77.
    2. Doğan, Ilgın & Lokman, Banu & Köksalan, Murat, 2022. "Representing the nondominated set in multi-objective mixed-integer programs," European Journal of Operational Research, Elsevier, vol. 296(3), pages 804-818.
    3. Özarık, Sami Serkan & Lokman, Banu & Köksalan, Murat, 2020. "Distribution based representative sets for multi-objective integer programs," European Journal of Operational Research, Elsevier, vol. 284(2), pages 632-643.

    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. H. P. Benson & E. Sun, 2000. "Outcome Space Partition of the Weight Set in Multiobjective Linear Programming," Journal of Optimization Theory and Applications, Springer, vol. 105(1), pages 17-36, April.
    2. Stacey Faulkenberg & Margaret Wiecek, 2012. "Generating equidistant representations in biobjective programming," Computational Optimization and Applications, Springer, vol. 51(3), pages 1173-1210, April.
    3. Murat Köksalan & Robert D. Plante, 2003. "Interactive Multicriteria Optimization for Multiple-Response Product and Process Design," Manufacturing & Service Operations Management, INFORMS, vol. 5(4), pages 334-347, May.
    4. 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.
    5. Markus Hirschberger & Ralph E. Steuer & Sebastian Utz & Maximilian Wimmer & Yue Qi, 2013. "Computing the Nondominated Surface in Tri-Criterion Portfolio Selection," Operations Research, INFORMS, vol. 61(1), pages 169-183, February.
    6. Hartikainen, Markus & Miettinen, Kaisa & Klamroth, Kathrin, 2019. "Interactive Nonconvex Pareto Navigator for multiobjective optimization," European Journal of Operational Research, Elsevier, vol. 275(1), pages 238-251.
    7. Ana B. Ruiz & Francisco Ruiz & Kaisa Miettinen & Laura Delgado-Antequera & Vesa Ojalehto, 2019. "NAUTILUS Navigator: free search interactive multiobjective optimization without trading-off," Journal of Global Optimization, Springer, vol. 74(2), pages 213-231, June.
    8. J. Fülöp & L. D. Muu, 2000. "Branch-and-Bound Variant of an Outcome-Based Algorithm for Optimizing over the Efficient Set of a Bicriteria Linear Programming Problem," Journal of Optimization Theory and Applications, Springer, vol. 105(1), pages 37-54, April.
    9. Thomas L. Saaty, 2013. "The Modern Science of Multicriteria Decision Making and Its Practical Applications: The AHP/ANP Approach," Operations Research, INFORMS, vol. 61(5), pages 1101-1118, October.
    10. Zanakis, Stelios H. & Mandakovic, Tomislav & Gupta, Sushil K. & Sahay, Sundeep & Hong, Sungwan, 1995. "A review of program evaluation and fund allocation methods within the service and government sectors," Socio-Economic Planning Sciences, Elsevier, vol. 29(1), pages 59-79, March.
    11. Arbel, Ami & Korhonen, Pekka, 2001. "Using objective values to start multiple objective linear programming algorithms," European Journal of Operational Research, Elsevier, vol. 128(3), pages 587-596, February.
    12. Akram Dehnokhalaji & Mojtaba Ghiyasi & Pekka Korhonen, 2017. "Resource allocation based on cost efficiency," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1279-1289, October.
    13. Tobias Kuhn & Stefan Ruzika, 2017. "A coverage-based Box-Algorithm to compute a representation for optimization problems with three objective functions," Journal of Global Optimization, Springer, vol. 67(3), pages 581-600, March.
    14. Korhonen, Pekka & Tainio, Risto & Wallenius, Jyrki, 2001. "Value efficiency analysis of academic research," European Journal of Operational Research, Elsevier, vol. 130(1), pages 121-132, April.
    15. Rennen, G. & van Dam, E.R. & den Hertog, D., 2009. "Enhancement of Sandwich Algorithms for Approximating Higher Dimensional Convex Pareto Sets," Other publications TiSEM e2255959-6691-4ef1-88a4-5, Tilburg University, School of Economics and Management.
    16. Pontes, Roberto Da Silva Gervasio & Brandão, Diego Nunes & Usberti, Fábio Luiz & De Assis, Laura Silva, 2024. "Multi-objective models for crop rotation planning problems," Agricultural Systems, Elsevier, vol. 219(C).
    17. Gabriele Eichfelder & Peter Kirst & Laura Meng & Oliver Stein, 2021. "A general branch-and-bound framework for continuous global multiobjective optimization," Journal of Global Optimization, Springer, vol. 80(1), pages 195-227, May.
    18. Liesiö, Juuso & Andelmin, Juho & Salo, Ahti, 2020. "Efficient allocation of resources to a portfolio of decision making units," European Journal of Operational Research, Elsevier, vol. 286(2), pages 619-636.
    19. Sylva, John & Crema, Alejandro, 2007. "A method for finding well-dispersed subsets of non-dominated vectors for multiple objective mixed integer linear programs," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1011-1027, August.
    20. Kathrin Klamroth & Kaisa Miettinen, 2008. "Integrating Approximation and Interactive Decision Making in Multicriteria Optimization," Operations Research, INFORMS, vol. 56(1), pages 222-234, February.

    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:inm:oropre:v:57:y:2009:i:1:p:187-199. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.