Optimizing OOH Media Plans Using Weighted Set Cover Algorithms

Media Plan Optimizations (MPOs) are frequently employed in the advertising industry. Given a variety of advertising spaces, the goal is to have an impact as high as possible while minimizing costs. Taking into account that each advertising space has a given cost and has its own viewers, and two spaces can share common viewers, this translates into a weighted set cover problem. Problems of this type are NP-complete, so there are no known polynomial-time exact algorithms for finding the optimal solution. An alternative is to use a Greedy algorithm, which offers a good approximation in a reasonable amount of time. In this paper, we study the mapping of the Media Plan Optimization problem to the Weighted Set Cover problem. We analyze the performance of the Backtracking and Greedy algorithms in respect to computational time and solution quality, under a wide range of OOH (Out-Of-Home) MPO scenarios. We evaluate the possibility of using these algorithms in a high availability, client-server Media Planning solution based on web services and find the computational performance and accuracy of the Greedy Algorithm to be adequate for the task.