par Pagnoncelli, Bernardo B.K.;Vanduffel, Steven
Référence European journal of operational research, 221, 2, page (445-453)
Publication Publié, 2012-09
Article révisé par les pairs
Résumé : We consider the problem of determining the minimal requirement one must establish in order to meet a series of future random payments. It is shown in a very general setting that this problem can be recast as a chance constrained model and how the technique of Sample Average Approximation can be employed to find solutions. We also use comonotonic theory to analyze analytical approximations in a restricted Gaussian setting. Our numerical illustrations demonstrate that the Sample Average Approximation is a viable and efficient way to solve the stated problem generally and outperforms the analytical approximations. In passing we present a result that is related to Stein's famous lemma (Stein, 1981) and is of interest in itself. © 2012 Elsevier B.V. All rights reserved.