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Mathematical models for the television advertising allocation problem

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  • Xinhui Zhang

Abstract

Television networks deliver television programming to the public free of charge; their primary source of revenue is the sale of advertising slots in their programmes. A key problem faced by the TV networks is how to allocate these slots to advertisers. The problem is complicated by sophisticated show structure, limited inventory of slots, demographics, show preferences and competition avoidance. In this paper, a two step hierarchical approach is proposed to solve this problem. This approach starts with a winner determination problem to select advertisers and assign them to shows and ends with a pod assignment problem to schedule commercials of the selected advertisers in a show. The winner determination problem is solved using column generation algorithm which was able to get near optimal solutions orders of magnitudes faster than the state-of-the-art B&B algorithm. The methodology proposed offers great potential for these networks to increase revenue.

Suggested Citation

  • Xinhui Zhang, 2006. "Mathematical models for the television advertising allocation problem," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 1(3), pages 302-322.
    • Handle: RePEc:ids:ijores:v:1:y:2006:i:3:p:302-322
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    Citations

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    Cited by:

    1. John Turner & Alan Scheller-Wolf & Sridhar Tayur, 2011. "OR PRACTICE---Scheduling of Dynamic In-Game Advertising," Operations Research, INFORMS, vol. 59(1), pages 1-16, February.
    2. Saravanan Venkatachalam & Fion Wong & Emrah Uyar & Stan Ward & Amit Aggarwal, 2015. "Media Company Uses Analytics to Schedule Radio Advertisement Spots," Interfaces, INFORMS, vol. 45(6), pages 485-500, December.
    3. Giovanni Giallombardo & Giovanna Miglionico & Houyuan Jiang, 2015. "New Reformulations for the Conflict Resolution Problem in the Scheduling of Television Commercials," Working Papers 2015/03, Cambridge Judge Business School, University of Cambridge.
    4. Victor F. Araman & Ioana Popescu, 2010. "Media Revenue Management with Audience Uncertainty: Balancing Upfront and Spot Market Sales," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 190-212, December.
    5. Giovanni Giallombardo & Houyuan Jiang & Giovanna Miglionico, 2016. "New Formulations for the Conflict Resolution Problem in the Scheduling of Television Commercials," Operations Research, INFORMS, vol. 64(4), pages 838-848, August.
    6. José Antonio Carbajal & Peter Williams & Andreea Popescu & Wes Chaar, 2019. "Turner Blazes a Trail for Audience Targeting on Television with Operations Research and Advanced Analytics," Interfaces, INFORMS, vol. 49(1), pages 64-89, January.
    7. Shinjini Pandey & Goutam Dutta & Harit Joshi, 2017. "Survey on Revenue Management in Media and Broadcasting," Interfaces, INFORMS, vol. 47(3), pages 195-213, June.
    8. José Antonio Carbajal & Wes Chaar, 2017. "Turner Optimizes the Allocation of Audience Deficiency Units," Interfaces, INFORMS, vol. 47(6), pages 518-536, December.

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