Design of Experiments under Constraints

This paper was done in collaboration between the System and Decision Sciences Area (SDS) and the Adaptive Resource Policy Project (ARP). It faces the problem of optimal experimental design. This problem arises in adaptive policy making at the stage of estimating a model's parameters. It can be considered as an optimization problem with both objective functions and constraints dependent upon probabilistic measures. Methods for dealing with such problems have recently been developed in SDS. In this paper, these methods are applied to optimal experimental design which allows us to get nontrivial results both in statistics and optimization theory.