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The Value of Information and Stochastic Programming

Author

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  • M. Avriel

    (Mobil Research and Development Corporation, Princeton, New Jersey)

  • A. C. Williams

    (Mobil Research and Development Corporation, Princeton, New Jersey)

Abstract

The problem of planning under uncertainty has many aspects; in this paper we consider the aspect that has to do with evaluating the state of information. We address ourselves to the question of how much better (i.e., how much more profitable) we could expect our plans to be if somehow we could know at planning time what the outcomes of the uncertain events will turn out to be. This expected increase in profitability is the “expected value of perfect information” and represents an upper bound to the amount of money that it would be worthwhile to spend in any survey or other investigation designed to provide that information beforehand. In many cases, the amount of calculation to compute an exact value is prohibitive. However, we derive bounds (estimates) for the value. Moreover, in the case of operations planning by linear or convex programming, we show how to evaluate these bounds as part of a post-optimal analysis.

Suggested Citation

  • M. Avriel & A. C. Williams, 1970. "The Value of Information and Stochastic Programming," Operations Research, INFORMS, vol. 18(5), pages 947-954, October.
    • Handle: RePEc:inm:oropre:v:18:y:1970:i:5:p:947-954
    DOI: 10.1287/opre.18.5.947
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