Sequential Search with Multiattribute Options

We describe a search problem in which a decision maker (DM) must select several sequentially-encountered options. Each option is described by multiple attributes, and the value of an option is given by a function of its attribute values. However, the attribute values are not known with certainty, and can only be ascertained in a predefined order, at some fixed cost. During the search the DM can choose to select an option, purchase information about an attribute value, reject (permanently) the current option and continue the search, or terminate the search and accept a status quo outcome. We introduce a Threshold Policy for this search process, and provide a class of option value functions for which the policy is optimal. We then furnish a dynamic programming procedure for prescribing an optimal policy for this problem. Finally, we derive analytic solutions to some special cases of the problem, and present a case study that demonstrates a possible use of the proposed approach.