IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v138y2002i2p274-293.html
   My bibliography  Save this article

Construction of rule-based assignment models

Author

Listed:
  • Azibi, R.
  • Vanderpooten, D.

Abstract

No abstract is available for this item.

Suggested Citation

  • Azibi, R. & Vanderpooten, D., 2002. "Construction of rule-based assignment models," European Journal of Operational Research, Elsevier, vol. 138(2), pages 274-293, April.
    • Handle: RePEc:eee:ejores:v:138:y:2002:i:2:p:274-293
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(01)00246-6
    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. R. Slowinski & C. Zopounidis, 1995. "Application of the Rough Set Approach to Evaluation of Bankruptcy Risk," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 4(1), pages 27-41, March.
    2. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
    3. Williams, H. P., 1995. "Logic applied to integer programming and integer programming applied to logic," European Journal of Operational Research, Elsevier, vol. 81(3), pages 605-616, March.
    4. Patrice Perny, 1998. "Multicriteria filtering methods based onconcordance and non-discordance principles," Annals of Operations Research, Springer, vol. 80(0), pages 137-165, January.
    5. Mitra, G. & Lucas, C. & Moody, S. & Hadjiconstantinou, E., 1994. "Tools for reformulating logical forms into zero-one mixed integer programs," European Journal of Operational Research, Elsevier, vol. 72(2), pages 262-276, January.
    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. Yuan Li & Xiuwu Liao & Wenhong Zhao, 2009. "A rough set approach to knowledge discovery in analyzing competitive advantages of firms," Annals of Operations Research, Springer, vol. 168(1), pages 205-223, April.
    2. Azibi, R. & Vanderpooten, D., 2003. "Aggregation of dispersed consequences for constructing criteria: The evaluation of flood risk reduction strategies," European Journal of Operational Research, Elsevier, vol. 144(2), pages 397-411, January.
    3. Sawicki, Piotr & Zak, Jacek, 2009. "Technical diagnostic of a fleet of vehicles using rough set theory," European Journal of Operational Research, Elsevier, vol. 193(3), pages 891-903, March.
    4. Denis Bouyssou & Marc Pirlot, 2004. "Preferences for multi-attributed alternatives: Traces, Dominance, and Numerical Representations," Post-Print hal-00004104, HAL.
    5. Shyng, Jhieh-Yu & Shieh, How-Ming & Tzeng, Gwo-Hshiung & Hsieh, Shu-Huei, 2010. "Using FSBT technique with Rough Set Theory for personal investment portfolio analysis," European Journal of Operational Research, Elsevier, vol. 201(2), pages 601-607, 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. 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.
    2. McKee, Thomas E. & Lensberg, Terje, 2002. "Genetic programming and rough sets: A hybrid approach to bankruptcy classification," European Journal of Operational Research, Elsevier, vol. 138(2), pages 436-451, April.
    3. Fernando García & Francisco Guijarro & Ismael Moya, 2013. "Monitoring credit risk in the social economy sector by means of a binary goal programming model," Service Business, Springer;Pan-Pacific Business Association, vol. 7(3), pages 483-495, September.
    4. Hui Hu & Milind Sathye, 2015. "Predicting Financial Distress in the Hong Kong Growth Enterprises Market from the Perspective of Financial Sustainability," Sustainability, MDPI, vol. 7(2), pages 1-15, January.
    5. Thomas E. Mckee, 2000. "Developing a bankruptcy prediction model via rough sets theory," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 9(3), pages 159-173, September.
    6. Low Sui Pheng & Jiang Hongbin, 2006. "Analysing ownership, locational and internalization advantages of Chinese construction MNCs using rough sets analysis," Construction Management and Economics, Taylor & Francis Journals, vol. 24(11), pages 1149-1165.
    7. Sawicki, Piotr & Zak, Jacek, 2009. "Technical diagnostic of a fleet of vehicles using rough set theory," European Journal of Operational Research, Elsevier, vol. 193(3), pages 891-903, March.
    8. Sanchis, A. & Segovia, M.J. & Gil, J.A. & Heras, A. & Vilar, J.L., 2007. "Rough Sets and the role of the monetary policy in financial stability (macroeconomic problem) and the prediction of insolvency in insurance sector (microeconomic problem)," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1554-1573, September.
    9. I Y-F Huang & W-W Wu & Y-T Lee, 2008. "Simplifying essential competencies for Taiwan civil servants using the rough set approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(2), pages 259-265, February.
    10. Thomas E. McKee, 2003. "Rough sets bankruptcy prediction models versus auditor signalling rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(8), pages 569-586.
    11. Tay, Francis E. H. & Shen, Lixiang, 2002. "Economic and financial prediction using rough sets model," European Journal of Operational Research, Elsevier, vol. 141(3), pages 641-659, September.
    12. Malcolm J. Beynon & Mark A. Clatworthy & Michael John Jones, 2004. "The prediction of profitability using accounting narratives: a variable‐precision rough set approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 12(4), pages 227-242, October.
    13. Beynon, Malcolm J. & Peel, Michael J., 2001. "Variable precision rough set theory and data discretisation: an application to corporate failure prediction," Omega, Elsevier, vol. 29(6), pages 561-576, December.
    14. Zopounidis, Constantin & Doumpos, Michael, 2001. "A preference disaggregation decision support system for financial classification problems," European Journal of Operational Research, Elsevier, vol. 130(2), pages 402-413, April.
    15. Zopounidis, C., 1999. "Multicriteria decision aid in financial management," European Journal of Operational Research, Elsevier, vol. 119(2), pages 404-415, December.
    16. Beynon, Malcolm, 2001. "Reducts within the variable precision rough sets model: A further investigation," European Journal of Operational Research, Elsevier, vol. 134(3), pages 592-605, November.
    17. Mak, Brenda & Munakata, Toshinori, 2002. "Rule extraction from expert heuristics: A comparative study of rough sets with neural networks and ID3," European Journal of Operational Research, Elsevier, vol. 136(1), pages 212-229, January.
    18. Michael Doumpos & Constantin Zopounidis, 1999. "A Multicriteria Discrimination Method for the Prediction of Financial Distress: The Case of Greece," Multinational Finance Journal, Multinational Finance Journal, vol. 3(2), pages 71-101, June.
    19. Rueben Laryea, 2013. "A multi-criteria prediction model for project risk classifications," International Journal of Decision Sciences, Risk and Management, Inderscience Enterprises Ltd, vol. 5(1), pages 55-79.
    20. Eduardo Fernández & José Rui Figueira & Jorge Navarro, 2023. "A theoretical look at ordinal classification methods based on comparing actions with limiting boundaries between adjacent classes," Annals of Operations Research, Springer, vol. 325(2), pages 819-843, June.

    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:138:y:2002:i:2:p:274-293. 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.