Abstract
We study the following online problem. Each advertiser a i has a value v i , demand d i , and frequency cap f i . Supply units arrive online, each one associated with a user. Each advertiser can be assigned at most d i units in all, and at most f i units from the same user. The goal is to design an online allocation algorithm maximizing total value.
We first show a deterministic upper bound of 3/4-competitiveness, 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 model with arbitrary decreasing valuations [GM07]. Our main contribution is analyzing two 3/4-competitive greedy algorithms for the cases of equal values, and arbitrary valuations with equal demands. Finally, we give a primal-dual algorithm which may serve as a good starting point for improving upon the 1 − 1/e ratio.
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Buchbinder, N., Feldman, M., Ghosh, A., Naor, J.(. (2011). Frequency Capping in Online Advertising. In: Dehne, F., Iacono, J., Sack, JR. (eds) Algorithms and Data Structures. WADS 2011. Lecture Notes in Computer Science, vol 6844. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22300-6_13
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DOI: https://doi.org/10.1007/978-3-642-22300-6_13
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