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On the Objective Function for the Sequential P-Model of Chance-Constrained Programming

Author

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  • Robert S. Kaplan

    (Carnegie-Mellon University, Pittsburgh, Pennsylvania)

  • John V. Soden

    (McKinsey and Company, Inc., Los Angeles, California)

Abstract

The P-model objective of chance-constrained programming reflects the desire of management to maximize the probability of achieving or exceeding a given level of performance. This paper explores the implications of being able to make a sequence of decisions with the P-model objective function, and introduces some new possibilities for the P-model objective function that arise from the sequential nature of the problem. However, it is shown that, except for a special form of the objective function, the maximization in the sequential problem is not of a quasiconcave function, so that local optimality conditions are not sufficient to guarantee that a proposed solution is a global optimum. An example is worked out in detail to illustrate the computations involved for the objectives considered.

Suggested Citation

  • Robert S. Kaplan & John V. Soden, 1971. "On the Objective Function for the Sequential P-Model of Chance-Constrained Programming," Operations Research, INFORMS, vol. 19(1), pages 105-114, February.
    • Handle: RePEc:inm:oropre:v:19:y:1971:i:1:p:105-114
    DOI: 10.1287/opre.19.1.105
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