IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v36y2008i3p373-383.html
   My bibliography  Save this article

A case-based distance method for screening in multiple-criteria decision aid

Author

Listed:
  • Chen, Ye
  • Marc Kilgour, D.
  • Hipel, Keith W.

Abstract

Screening is a process of multiple-criteria decision aid (MCDA) in which a large set of alternatives is reduced to a smaller set that most likely contains the best choice. We propose screening using a distance model calibrated on the basis of the decision-maker's own judgement. Viewing MCDA as preference aggregation based on consequence data, we define consequence and preference expressions (values and weights) and describe how they are aggregated. Then we define screening and explain some of its properties. Using an appropriate definition of distance, our case-based distance method screens a set of alternatives using criterion weights and a distance threshold obtained by quadratic optimization using the decision-maker's selection of alternatives from a test set. This case-based method can elicit the decision maker's preferences more expeditiously and accurately than direct inquiry. An application in water supply planning is used to demonstrate the procedure.

Suggested Citation

  • Chen, Ye & Marc Kilgour, D. & Hipel, Keith W., 2008. "A case-based distance method for screening in multiple-criteria decision aid," Omega, Elsevier, vol. 36(3), pages 373-383, June.
    • Handle: RePEc:eee:jomega:v:36:y:2008:i:3:p:373-383
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305-0483(06)00121-6
    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. Jacquet-Lagreze, E. & Siskos, J., 1982. "Assessing a set of additive utility functions for multicriteria decision-making, the UTA method," European Journal of Operational Research, Elsevier, vol. 10(2), pages 151-164, June.
    2. Insua, David Rios & French, Simon, 1991. "A framework for sensitivity analysis in discrete multi-objective decision-making," European Journal of Operational Research, Elsevier, vol. 54(2), pages 176-190, September.
    3. Jacquet-Lagreze, Eric & Siskos, Yannis, 2001. "Preference disaggregation: 20 years of MCDA experience," European Journal of Operational Research, Elsevier, vol. 130(2), pages 233-245, April.
    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. Vetschera, Rudolf & Chen, Ye & Hipel, Keith W. & Marc Kilgour, D., 2010. "Robustness and information levels in case-based multiple criteria sorting," European Journal of Operational Research, Elsevier, vol. 202(3), pages 841-852, May.
    2. Wu, Siqi & Wu, Meng & Dong, Yucheng & Liang, Haiming & Zhao, Sihai, 2020. "The 2-rank additive model with axiomatic design in multiple attribute decision making," European Journal of Operational Research, Elsevier, vol. 287(2), pages 536-545.
    3. Jessop, Alan, 2014. "IMP: A decision aid for multiattribute evaluation using imprecise weight estimates," Omega, Elsevier, vol. 49(C), pages 18-29.
    4. Michael D. Gerst & Melissa A. Kenney & Brett E. Howard & Robert J. Giraud, 2020. "A decision‐analytic approach to screening in chemical alternatives assessment," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1597-1604, March.
    5. Liu, Jiapeng & Liao, Xiuwu & Kadziński, Miłosz & Słowiński, Roman, 2019. "Preference disaggregation within the regularization framework for sorting problems with multiple potentially non-monotonic criteria," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1071-1089.
    6. Ma, Li-Ching, 2012. "Screening alternatives graphically by an extended case-based distance approach," Omega, Elsevier, vol. 40(1), pages 96-103, January.
    7. Sevastjanov, Pavel & Dymova, Ludmila, 2009. "Stock screening with use of multiple criteria decision making and optimization," Omega, Elsevier, vol. 37(3), pages 659-671, June.
    8. Liu, Jiapeng & Liao, Xiuwu & Yang, Jian-bo, 2015. "A group decision-making approach based on evidential reasoning for multiple criteria sorting problem with uncertainty," European Journal of Operational Research, Elsevier, vol. 246(3), pages 858-873.
    9. Aydin, Nezir & Celik, Erkan & Gumus, Alev Taskin, 2015. "A hierarchical customer satisfaction framework for evaluating rail transit systems of Istanbul," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 61-81.
    10. Li, Sheng-Tun & Chou, Wei-Chien, 2014. "Power planning in ICT infrastructure: A multi-criteria operational performance evaluation approach," Omega, Elsevier, vol. 49(C), pages 134-148.
    11. Doumpos, Michael & Zopounidis, Constantin, 2011. "Preference disaggregation and statistical learning for multicriteria decision support: A review," European Journal of Operational Research, Elsevier, vol. 209(3), pages 203-214, March.

    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. Kadziński, Miłosz & Wójcik, Michał & Ciomek, Krzysztof, 2022. "Review and experimental comparison of ranking and choice procedures for constructing a univocal recommendation in a preference disaggregation setting," Omega, Elsevier, vol. 113(C).
    2. Grigoroudis, Evangelos & Noel, Laurent & Galariotis, Emilios & Zopounidis, Constantin, 2021. "An ordinal regression approach for analyzing consumer preferences in the art market," European Journal of Operational Research, Elsevier, vol. 290(2), pages 718-733.
    3. Zopounidis, Constantin & Doumpos, Michael, 2002. "Multicriteria classification and sorting methods: A literature review," European Journal of Operational Research, Elsevier, vol. 138(2), pages 229-246, April.
    4. Angilella, Silvia & Greco, Salvatore & Matarazzo, Benedetto, 2010. "Non-additive robust ordinal regression: A multiple criteria decision model based on the Choquet integral," European Journal of Operational Research, Elsevier, vol. 201(1), pages 277-288, February.
    5. Hurson, Christian & Siskos, Yannis, 2014. "A synergy of multicriteria techniques to assess additive value models," European Journal of Operational Research, Elsevier, vol. 238(2), pages 540-551.
    6. Arcidiacono, Sally Giuseppe & Corrente, Salvatore & Greco, Salvatore, 2021. "Robust stochastic sorting with interacting criteria hierarchically structured," European Journal of Operational Research, Elsevier, vol. 292(2), pages 735-754.
    7. Bous, Géraldine & Fortemps, Philippe & Glineur, François & Pirlot, Marc, 2010. "ACUTA: A novel method for eliciting additive value functions on the basis of holistic preference statements," European Journal of Operational Research, Elsevier, vol. 206(2), pages 435-444, October.
    8. Wątróbski, Jarosław & Jankowski, Jarosław & Ziemba, Paweł & Karczmarczyk, Artur & Zioło, Magdalena, 2019. "Generalised framework for multi-criteria method selection," Omega, Elsevier, vol. 86(C), pages 107-124.
    9. Eskantar, Marianna & Zopounidis, Constantin & Doumpos, Michalis & Galariotis, Emilios & Guesmi, Khaled, 2024. "Navigating ESG complexity: An in-depth analysis of sustainability criteria, frameworks, and impact assessment," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    10. Ciomek, Krzysztof & Kadziński, Miłosz & Tervonen, Tommi, 2017. "Heuristics for selecting pair-wise elicitation questions in multiple criteria choice problems," European Journal of Operational Research, Elsevier, vol. 262(2), pages 693-707.
    11. Wu, Siqi & Wu, Meng & Dong, Yucheng & Liang, Haiming & Zhao, Sihai, 2020. "The 2-rank additive model with axiomatic design in multiple attribute decision making," European Journal of Operational Research, Elsevier, vol. 287(2), pages 536-545.
    12. Dias, Luis C. & Dias, Joana & Ventura, Tiago & Rocha, Humberto & Ferreira, Brígida & Khouri, Leila & Lopes, Maria do Carmo, 2022. "Learning target-based preferences through additive models: An application in radiotherapy treatment planning," European Journal of Operational Research, Elsevier, vol. 302(1), pages 270-279.
    13. Gehrlein, Jonas & Miebs, Grzegorz & Brunelli, Matteo & Kadziński, Miłosz, 2023. "An active preference learning approach to aid the selection of validators in blockchain environments," Omega, Elsevier, vol. 118(C).
    14. Mousseau, Vincent & Dias, Luis, 2004. "Valued outranking relations in ELECTRE providing manageable disaggregation procedures," European Journal of Operational Research, Elsevier, vol. 156(2), pages 467-482, July.
    15. Kubińska, Elżbieta & Adamczyk-Kowalczuk, Magdalena & Andrzejewski, Mariusz & Rozakis, Stelios, 2022. "Incorporating the status quo effect into the decision making process: The case of municipal companies merger," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    16. Sobrie, Olivier & Gillis, Nicolas & Mousseau, Vincent & Pirlot, Marc, 2018. "UTA-poly and UTA-splines: Additive value functions with polynomial marginals," European Journal of Operational Research, Elsevier, vol. 264(2), pages 405-418.
    17. Marinakis, Vangelis & Doukas, Haris & Xidonas, Panos & Zopounidis, Constantin, 2017. "Multicriteria decision support in local energy planning: An evaluation of alternative scenarios for the Sustainable Energy Action Plan," Omega, Elsevier, vol. 69(C), pages 1-16.
    18. Samaras, Georgios D. & Matsatsinis, Nikolaos F. & Zopounidis, Constantin, 2008. "A multicriteria DSS for stock evaluation using fundamental analysis," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1380-1401, June.
    19. Brito, Anderson J. & de Almeida, Adiel T., 2012. "Modeling a multi-attribute utility newsvendor with partial backlogging," European Journal of Operational Research, Elsevier, vol. 220(3), pages 820-830.
    20. Lourenco, Rui Pedro & Costa, Joao Paulo, 2004. "Using ELECTRE TRI outranking method to sort MOMILP nondominated solutions," European Journal of Operational Research, Elsevier, vol. 153(2), pages 271-289, March.

    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:jomega:v:36:y:2008:i:3:p:373-383. 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/wps/find/journaldescription.cws_home/375/description#description .

    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.