Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23259
Title: Utility-maximizing resource control : diffusion limit and asymptotic optimality for a two-bottleneck model
Authors: Ye, HQ 
Yao, DD
Issue Date: 2010
Publisher: Institute for Operations Research and the Management Sciences
Source: Operations research, 2010, v. 58, no. 3, p. 613-623 How to cite?
Journal: Operations research 
Abstract: Stochastic programming can effectively describe many decision-making problems in uncertain environments. Unfortunately,such programs are often computationally demanding to solve. In addition, their solution can be misleading when there is ambiguity in the choice of a distribution for the random parameters. In this paper, we propose a model that describes uncertainty in both the distribution form (discrete, Gaussian, exponential, etc.) and moments (mean and covariance matrix). We demonstrate that for a wide range of cost functions the associated distributionally robust (or min-max) stochastic program can be solved efficiently. Furthermore, by deriving a new confidence region for the mean and the covariance matrix of a random vector, we provide probabilistic arguments for using our model in problems that rely heavily on historical data. These arguments are confirmed in a practical example of portfolio selection, where our framework leads to better-performing policies on the "true" distribution underlying the daily returns of financial assets.
URI: http://hdl.handle.net/10397/23259
ISSN: 0030-364x
EISSN: 1526-5463
DOI: 10.1287/opre.1090.0758
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