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Approximations and Sensitivity in Multiobjective Resource Allocation

Author

Listed:
  • Donald L. Keefer

    (Gulf Oil Corporation, Pittsburgh, Pennsylvania)

  • Stephen M. Pollock

    (University of Michigan, Ann Arbor, Michigan)

Abstract

This paper addresses the modeling of resource allocation planning problems having uncertainties, multiple competing objectives, organizational constraints, and continuous decision variables. The application of multiobjective decision analysis leads to a nonlinear programming formulation in which the objective function is the expectation of a multiattribute utility function. If a set of independence conditions holds, this function can be decomposed into appropriately scaled sums and products of one-dimensional expected utility functions. Approximations that greatly simplify the data acquisition for, and the construction of, the one-dimensional expected utility functions are discussed. Sensitivity analyses indicate that optimal solutions to such models are robust with respect to changes in the required data, but may be seriously in error if certain popular, but overly simplified, forms for the objective function are assumed.

Suggested Citation

  • Donald L. Keefer & Stephen M. Pollock, 1980. "Approximations and Sensitivity in Multiobjective Resource Allocation," Operations Research, INFORMS, vol. 28(1), pages 114-128, February.
    • Handle: RePEc:inm:oropre:v:28:y:1980:i:1:p:114-128
    DOI: 10.1287/opre.28.1.114
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    Cited by:

    1. Jesse Daniels & Paul W. Werner & A. Terry Bahill, 2001. "Quantitative methods for tradeoff analyses," Systems Engineering, John Wiley & Sons, vol. 4(3), pages 190-212.
    2. Terry P. Harrison & Richard E. Rosenthal, 1988. "Optimizability of utility and value functions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(3), pages 411-418, June.
    3. Peter H. Farquhar & Yutaka Nakamura, 1988. "Utility assessment procedures for polynomial‐exponential functions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(6), pages 597-613, December.
    4. Rosenbloom, E. S., 1997. "A probabilistic interpretation of the final rankings in AHP," European Journal of Operational Research, Elsevier, vol. 96(2), pages 371-378, January.
    5. Philip O. Beck & Gary Klein, 1989. "Determining restrictive goals in linear goal programs," Naval Research Logistics (NRL), John Wiley & Sons, vol. 36(5), pages 675-682, October.

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