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A Progressive Algorithm for Modeling and Solving Multiple-Criteria Decision Problems

Author

Listed:
  • Pekka Korhonen

    (Helsinki School of Economics, Helsinki, Finland)

  • Herbert Moskowitz

    (Purdue University, West Lafayette, Indiana, and the London Business School, London, England)

  • Jyrki Wallenius

    (Arizona State University, Tempe, Arizona, and the University of Jyvaskyla, Finland)

Abstract

We consider a decision maker (DM) who has a set of possible decision alternatives, from which one (a “best”) is to be chosen. However, all decision alternatives are not at the DM's disposal initially, nor is full knowledge of his/her utility/value function. Therefore, the DM evaluates only the available subset of all decision alternatives, from which he/she chooses a most preferred one. Obviously, this decision is not necessarily “globally” best. Two natural questions arise: How good is the most preferred solution? What are the chances of finding better solutions by considering additional alternatives? We describe and illustrate a general progressive algorithm and the supporting theory for modeling and solving this problem when alternatives are introduced dynamically.

Suggested Citation

  • Pekka Korhonen & Herbert Moskowitz & Jyrki Wallenius, 1986. "A Progressive Algorithm for Modeling and Solving Multiple-Criteria Decision Problems," Operations Research, INFORMS, vol. 34(5), pages 726-731, October.
    • Handle: RePEc:inm:oropre:v:34:y:1986:i:5:p:726-731
    DOI: 10.1287/opre.34.5.726
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    Citations

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    Cited by:

    1. Chun, Young H. & Sumichrast, Robert T., 2006. "A rank-based approach to the sequential selection and assignment problem," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1338-1344, October.
    2. Pekka Salminen & Jeffrey E. Teich & Jyrki Wallenius, 1998. "The Secretary Problem Revisited - The Group Decision-Making Perspective," Group Decision and Negotiation, Springer, vol. 7(1), pages 3-21, January.
    3. Soleimani-damaneh, Majid & Pourkarimi, Latif & Korhonen, Pekka J. & Wallenius, Jyrki, 2021. "An operational test for the existence of a consistent increasing quasi-concave value function," European Journal of Operational Research, Elsevier, vol. 289(1), pages 232-239.
    4. Ankur Sinha & Pekka Korhonen & Jyrki Wallenius, 2016. "Finding better alternatives than those considered in a multiple criteria data sample," Journal of Business Economics, Springer, vol. 86(1), pages 35-54, January.
    5. Nikolaos Argyris & Alec Morton & José Rui Figueira, 2014. "CUT: A Multicriteria Approach for Concavifiable Preferences," Operations Research, INFORMS, vol. 62(3), pages 633-642, June.
    6. Stein, William E. & Seale, Darryl A. & Rapoport, Amnon, 2003. "Analysis of heuristic solutions to the best choice problem," European Journal of Operational Research, Elsevier, vol. 151(1), pages 140-152, November.
    7. Lahdelma, Risto & Salminen, Pekka & Kuula, Markku, 2003. "Testing the efficiency of two pairwise comparison methods in discrete multiple criteria problems," European Journal of Operational Research, Elsevier, vol. 145(3), pages 496-508, March.
    8. Y H Chun, 2004. "Generalized best choice problem based on the information economics approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 988-999, September.
    9. Nasim Nasrabadi & Akram Dehnokhalaji & Pekka Korhonen & Jyrki Wallenius, 2019. "Using convex preference cones in multiple criteria decision making and related fields," Journal of Business Economics, Springer, vol. 89(6), pages 699-717, August.
    10. Canan Ulu & Murat Köksalan, 2001. "An interactive procedure for selecting acceptable alternatives in the presence of multiple criteria," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(7), pages 592-606, October.
    11. Chun, Young H., 2015. "Multi-attribute sequential decision problem with optimizing and satisficing attributes," European Journal of Operational Research, Elsevier, vol. 243(1), pages 224-232.

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