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Scheduling online advertisements to maximize revenue under variable display frequency


  • Deane, Jason
  • Agarwal, Anurag


The online advertising industry realized annual revenues estimated at over $26 billion, in the United States alone, in 2010. Banner advertising accounts for an estimated 23% of all online advertising revenues. Publishers of banner advertisements face a scheduling optimization problem on a daily basis. Several papers in the literature have proposed mathematical models and solution approaches to address a publisher's banner advertisement scheduling problem and the problem has been shown to be NP-hard. In this paper we propose a new model variation for the problem, which incorporates variable display frequencies. We find that the variable-display frequency model provides significantly improved space utilization relative to the fixed-display frequency model and consequently higher revenues for the publishers.

Suggested Citation

  • Deane, Jason & Agarwal, Anurag, 2012. "Scheduling online advertisements to maximize revenue under variable display frequency," Omega, Elsevier, vol. 40(5), pages 562-570.
  • Handle: RePEc:eee:jomega:v:40:y:2012:i:5:p:562-570 DOI: 10.1016/

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    Cited by:

    1. Beltran-Royo, C. & Escudero, L.F. & Zhang, H., 2016. "Multiperiod Multiproduct Advertising Budgeting: Stochastic Optimization Modeling," Omega, Elsevier, vol. 59(PA), pages 26-39.
    2. Deza, Antoine & Huang, Kai & Metel, Michael R., 2015. "Chance constrained optimization for targeted Internet advertising," Omega, Elsevier, vol. 53(C), pages 90-96.
    3. Ballings, Michel & Van den Poel, Dirk & Bogaert, Matthias, 2016. "Social media optimization: Identifying an optimal strategy for increasing network size on Facebook," Omega, Elsevier, vol. 59(PA), pages 15-25.
    4. Shah, Nita H & Soni, Hardik N & Patel, Kamlesh A, 2013. "Optimizing inventory and marketing policy for non-instantaneous deteriorating items with generalized type deterioration and holding cost rates," Omega, Elsevier, vol. 41(2), pages 421-430.
    5. H. Mirzaei, Fouad & Ødegaard, Fredrik & Yan, Xinghao, 2015. "User reward programs in online social media," Omega, Elsevier, vol. 57(PB), pages 123-144.


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