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Entropy‐based selection with multiple objectives

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  • F. Hutton Barron
  • Charles P. Schmidt

Abstract

In this article we present an approach to determine the initially unspecified weights in an additive measurable multiattribute value function. We formulate and solve a series of nonlinear programming problems which (1) incorporate whatever partial information concerning the attribute weights or overall relative value of alternatives the decision maker chooses to provide, yet (2) yield a specific set of weights as a result. Although each formulation is rather easily solved using the nonlinear programming software GINO (general interactive optimizer), solutions in closed form dependent on a single parameter are also provided for a number of these problems.

Suggested Citation

  • F. Hutton Barron & Charles P. Schmidt, 1988. "Entropy‐based selection with multiple objectives," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(6), pages 643-654, December.
    • Handle: RePEc:wly:navres:v:35:y:1988:i:6:p:643-654
    DOI: 10.1002/1520-6750(198812)35:63.0.CO;2-#
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    References listed on IDEAS

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    1. James S. Dyer & Rakesh K. Sarin, 1979. "Measurable Multiattribute Value Functions," Operations Research, INFORMS, vol. 27(4), pages 810-822, August.
    2. Craig W. Kirkwood & Rakesh K. Sarin, 1985. "Ranking with Partial Information: A Method and an Application," Operations Research, INFORMS, vol. 33(1), pages 38-48, February.
    3. Peter C. Fishburn, 1965. "Analysis of Decisions with Incomplete Knowledge of Probabilities," Operations Research, INFORMS, vol. 13(2), pages 217-237, April.
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