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

Robert S. Kaplan and John V. Soden
Additional contact information
Robert S. Kaplan: Carnegie-Mellon University, Pittsburgh, Pennsylvania
John V. Soden: McKinsey and Company, Inc., Los Angeles, California

Operations Research, 1971, vol. 19, issue 1, 105-114

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.

Date: 1971
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/opre.19.1.105 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:19:y:1971:i:1:p:105-114

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().