Journal of Applied Mathematics and Decision Sciences
Volume 4 (2000), Issue 1, Pages 17-38
Stratified filtered sampling in stochastic optimization
1Investment policy and Research Group, John Hancok Mutual Life Insurance Company, boston, massachusetts, USA
2Princeton University Princeton, NJ, USA
3Rensselaer Polytechnic Institute, Troy, New York, USA
Copyright © 2000 Robert Rush et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
We develop a methodology for evaluating a decision strategy
generated by a stochastic optimization model. The methodology is
based on a pilot study in which we estimate the distribution of
performance associated with the strategy, and define an appropriate
stratified sampling plan. An algorithm we call filtered search
allows us to implement this plan efficiently. We demonstrate the
approach's advantages with a problem in asset / liability management
for an insurance company.