Optimal Design of Optimization Experiments

Experimental optimization methods are used to determine optimal decision policies in the cases where the functional form or parameter values are unknown. The optimal design of such experiments is developed in this paper for a variety of methods of experimentation. Parameter values are estimated, an optimal decision policy is obtained, and estimates of the expected gain from experimentation are derived. Expected gains are compared for alternative experimental designs. In particular, methods are derived for obtaining the optimal size, organization structure, and duration time of the experiment. The general methods are applied to the problem of design of a maintenance experiment to obtain the scheduled maintenance frequency that achieves maximum cost savings.