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Preference Programming with incomplete ordinal information

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  • Punkka, Antti
  • Salo, Ahti

Abstract

This paper extends possibilities for analyzing incomplete ordinal information about the parameters of an additive value function. Such information is modeled through preference statements which associate sets of alternatives or attributes with corresponding sets of rankings. These preference statements can be particularly helpful in developing a joint preference representation for a group of decision-makers who may find difficulties in agreeing on numerical parameter values. Because these statements can lead to a non-convex set of feasible parameters, a mixed integer linear formulation is developed to establish a linear model for the computation of decision recommendations. This makes it possible to complete incomplete ordinal information with other forms of incomplete information.

Suggested Citation

  • Punkka, Antti & Salo, Ahti, 2013. "Preference Programming with incomplete ordinal information," European Journal of Operational Research, Elsevier, vol. 231(1), pages 141-150.
    • Handle: RePEc:eee:ejores:v:231:y:2013:i:1:p:141-150
    DOI: 10.1016/j.ejor.2013.05.003
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    Cited by:

    1. Harju, Mikko & Liesiö, Juuso & Virtanen, Kai, 2019. "Spatial multi-attribute decision analysis: Axiomatic foundations and incomplete preference information," European Journal of Operational Research, Elsevier, vol. 275(1), pages 167-181.
    2. Tom Pape, 2020. "Value of agreement in decision analysis: Concept, measures and application," Papers 2012.13816, arXiv.org.
    3. Wang, Zhou-Jing, 2015. "A note on “A goal programming model for incomplete interval multiplicative preference relations and its application in group decision-making”," European Journal of Operational Research, Elsevier, vol. 247(3), pages 867-871.
    4. Pape, Tom, 2017. "Value of agreement in decision analysis: concept, measures and application," LSE Research Online Documents on Economics 68682, London School of Economics and Political Science, LSE Library.
    5. Cinelli, Marco & Kadziński, Miłosz & Miebs, Grzegorz & Gonzalez, Michael & Słowiński, Roman, 2022. "Recommending multiple criteria decision analysis methods with a new taxonomy-based decision support system," European Journal of Operational Research, Elsevier, vol. 302(2), pages 633-651.
    6. Wenjun Chang & Chao Fu & Nanping Feng & Shanlin Yang, 2021. "Multi-criteria Group Decision Making with Various Ordinal Assessments," Group Decision and Negotiation, Springer, vol. 30(6), pages 1285-1314, December.
    7. Liesiö, Juuso & Punkka, Antti, 2014. "Baseline value specification and sensitivity analysis in multiattribute project portfolio selection," European Journal of Operational Research, Elsevier, vol. 237(3), pages 946-956.
    8. Adiel T. Almeida-Filho & Adiel T. Almeida & Ana Paula C. S. Costa, 2017. "A flexible elicitation procedure for additive model scale constants," Annals of Operations Research, Springer, vol. 259(1), pages 65-83, December.
    9. Antti Punkka & Ahti Salo, 2014. "Scale Dependence and Ranking Intervals in Additive Value Models Under Incomplete Preference Information," Decision Analysis, INFORMS, vol. 11(2), pages 83-104, June.
    10. Kadziński, Miłosz & Ciomek, Krzysztof & Słowiński, Roman, 2015. "Modeling assignment-based pairwise comparisons within integrated framework for value-driven multiple criteria sorting," European Journal of Operational Research, Elsevier, vol. 241(3), pages 830-841.

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