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Scheduling Online Advertisements to Maximize Revenue under Non-Linear Pricing
Journal article   Peer reviewed

Scheduling Online Advertisements to Maximize Revenue under Non-Linear Pricing

Jason Deane and Anurag Agarwal
The Journal of computer information systems, Vol.53(2), pp.85-92
12-01-2012

Abstract

Heuristics Non-Linear Pricing Optimization Pricing Discounts Scheduling
Internet popularity is at an all time high. This phenomenon continues to drive enormous revenue growth for the online advertising industry. One of the difficult challenges facing this industry is determining how to schedule online advertisements. We extend prior research in this area by developing a quantitative model which incorporates a very important economic strategy, volume pricing discounts. In addition, motivated by the NP-Hard nature of the problem, we propose and test a several heuristic and metaheuristic solution approaches. We show that explicit consideration of this economic pricing strategy in the scheduling process can, under certain elasticity of demand assumptions, significantly improve the revenue generation ability of online ad publishers. This provides significant support for the proposed model.

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