Encyclopedia of Operations Research and Management Science

2001 Edition
| Editors: Saul I. Gass, Carl M. Harris

Multi-attribute utility theory

  • Rakesh K. Sarin
Reference work entry
DOI: https://doi.org/10.1007/1-4020-0611-X_644

Consider a decision problem such as selection of a job, choice of an automobile, or resource allocation in a public program (education, health, criminal justice, etc.). These problems share a common feature—decision alternatives impact multiple attributes. The attractiveness of an alternative therefore depends on how well it scores on each attribute of interest and the relative importance of these attributes. Multi-attribute utility theory (MAUT) is useful in quantifying relative attractiveness of multi-attribute alternatives.

The following notation is useful:
  • Xi The set of outcomes (scores, consequences) on the ith attribute

  • xi A specific outcome in Xi

  • XX1 × X2 ×... × Xn (Cartesian product)

  • ui A single attribute utility function ui: XiOpen image in new window

This is a preview of subscription content, log in to check access.

References

  1. [1]
    Debreu, G. (1960). “Topological Methods in Cardinal Utility Theory,” in Mathematical Methods in the Social Sciences. Stanford University Press, Stanford, California, 16–26.Google Scholar
  2. [2]
    Dyer, J.S. and Sarin, R.K. (1979). “Measurable Multi-attribute Value Functions,” Operations Research, 27, 810–822.Google Scholar
  3. [3]
    Farquhar, P.H. (1977). “A Survey of Multiattribute Utility Theory and Applications,” TIMS Stud. Management Science, 6, 59–89.Google Scholar
  4. [4]
    Fishburn, P.C. (1964). Decision and Value Theory. Wiley, New York.Google Scholar
  5. [5]
    Fishburn, P.C. (1965a). “Independence in Utility Theory with Whole Product Sets,” Operations Research, 13, 28–45.Google Scholar
  6. [6]
    Fishburn, P.C. (1965b). “Utility Theory,” Management Science, 14, 335–378.Google Scholar
  7. [7]
    Gorman, W.M. (1968). “Symposium on Aggregation: The Structure of Utility Functions,” Rev. Econ. Stud., 35, 367–390.Google Scholar
  8. [8]
    Keeney, R.L. (1969). Multidimensional Utility Functions: Theory, Assessment, and Applications. Technical Report No. 43, Operations Research Center, M.I.T., Cambridge, Massachusetts. Google Scholar
  9. [9]
    Keeney, R.L. and Raiffa, H. (1976). Decisions with Multiple Objectives: Preferences and Value Trade-offs. Wiley, New York. Google Scholar
  10. [10]
    Luce, R.D. and Tukey, J.W. (1964). “Simultaneous Conjoint Measurement: A New type of Fundamental Measurement,” Jl. Math Psychol., 1, 1–27.Google Scholar
  11. [11]
    Luce, R.D., Bush, R.R., and Galantor, E. (1965). Handbook of Mathematical Psychology, Vol. 3. Wiley, New York.Google Scholar
  12. [12]
    Sarin, R.K. (1975). “Interactive Procedures for Evaluation of Multi-Attributed Alternatives.” Working Paper 232, Western Management Science Institute, University of California, Los Angeles.Google Scholar
  13. [13]
    von Neumann, J. and Morgenstern, O. (1947). Theory of Games and Economic Behavior, Princeton University Press, New Jersey.Google Scholar
  14. [14]
    Edwards, W. and von Winterfeldt, D. (1986). Decision Analysis and Behavioral Research. Cambridge University Press, Cambridge, England.Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Rakesh K. Sarin
    • 1
  1. 1.University of CaliforniaLos AngelesUSA