Frequency capping in online advertising

We study the following online problem. There are n advertisers. Each advertiser \(a_i\) has a total demand \(d_i\) and a value \(v_i\) for each supply unit. Supply units arrive one by one in an online fashion, and must be allocated to an agent immediately. Each unit is associated with a user, and each advertiser \(a_i\) is willing to accept no more than \(f_i\) units associated with any single user (the value \(f_i\) is called the frequency cap of advertiser \(a_i\)). The goal is to design an online allocation algorithm maximizing the total value. We first show a deterministic \(3/4\)-competitiveness upper bound, which holds even when all frequency caps are \(1\), and all advertisers share identical values and demands. A competitive ratio approaching \(1-1/e\) can be achieved via a reduction to a different model considered by Goel and Mehta (WINE ‘07: Workshop on Internet and Network, Economics: 335–340, 2007). Our main contribution is analyzing two \(3/4\)-competitive greedy algorithms for the cases of equal values, and arbitrary valuations with equal integral demand to frequency cap ratios. Finally, we give a primal-dual algorithm which may serve as a good starting point for improving upon the ratio of \(1-1/e\).