A Branch and Bound Algorithm for the List Selection Problem in Direct Mail Advertising

This paper describes a branch and bound approach for optimizing a media selection problem, namely, to choose the best set of mailing lists to maximize audience reach and exploits current heuristic approaches which improve computational efficiency.

Abstract

This paper describes a branch and bound approach for optimizing a media selection problem, namely, to choose the best set of mailing lists to maximize audience reach. Prompted by a national retailer's interest in more effective and efficient direct mail catalogue distribution, the algorithm exploits current heuristic approaches which improve computational efficiency. A numerical example and computational experience using actual data are discussed, along with extensions to other practical situations.