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Optimal display-ad allocation with guaranteed contracts and supply side platforms
- Source :
- Computers & Industrial Engineering, 137:106071. Elsevier
- Publication Year :
- 2019
-
Abstract
- We study a variant of the display-ad allocation problem where an online publisher needs to decide which subset of advertisement slots should be used in order to fulfill guaranteed contracts and which subset should be sold on supply side platforms (SSPs) in order to maximize the expected revenue. Our modeling approach also takes the uncertainty associated with the sale of an impression by an SSP into account. The way that information is revealed over time allows us to model the display-ad allocation problem as a two-stage stochastic program. We refer to our model as the Stochastic Programming (SP) model. Numerical experiments show that the SP model performs well in most cases. We compare the solutions of the SP model with the solutions of an allocation policy (the Priority Assignment (PA) heuristic) that is used in practice. We find that the performance gap between the PA heuristic and the SP model depends on the fraction of total impressions that need to be allocated to the guaranteed contracts. The results suggest that the benefit of using the SP model is highest in periods where the website traffic is high compared with the targets for the guaranteed contracts.
- Subjects :
- Mathematical optimization
021103 operations research
General Computer Science
business.industry
Heuristic
Computer science
0211 other engineering and technologies
General Engineering
Online advertising
Stochastic programming
Supply side platforms
Integer programming
02 engineering and technology
Supply side
Display-ad allocation
Order (business)
0202 electrical engineering, electronic engineering, information engineering
Revenue
020201 artificial intelligence & image processing
Fraction (mathematics)
business
Subjects
Details
- Language :
- English
- ISSN :
- 03608352
- Database :
- OpenAIRE
- Journal :
- Computers & Industrial Engineering, 137:106071. Elsevier
- Accession number :
- edsair.doi.dedup.....0134ca7d261297115c1c08d1d11be52a