Optimal screening designs with flexible cost and constraint structures

We describe a cost- and constraint-based decision-theoretic approach to the design of screening trials, where the goal is to identify promising candidates for future study or to decide whether to accept or reject a product. An algorithmic method for optimizing this approach is presented. This method utilizes a highly flexible structure to reflect a variety of decision and experimental costs and constraints. The designs produced can range from being a single stage up to being fully sequential, depending on the sampling cost functions and constraints. These designs generalize and extend those previously available, often achieving meaningful improvements. This approach can be used for a variety of other problems. Operating characteristics of the designs are also described.