Knapsack auctions

Gagan Aggarwal*, Jason D. Hartline

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

72 Scopus citations


We consider a game theoretic knapsack problem that has application to auctions for selling advertisements on Internet search engines. Consider n agents each wishing to place an object in the knapsack. Each agent has a private valuation for having their object in the knapsack and each object has a publicly known size. For this setting, we consider the design of auctions in which agents have an incentive to truthfully reveal their private valuations. Following the framework of Goldberg et al. [10], we look to design an auction that obtains a constant fraction of the profit obtainable by a natural optimal pricing algorithm that knows the agents' valuations and object sizes. We give an auction that obtains a constant factor approximation in the non-trivial special case where the knapsack has unlimited capacity. We then reduce the limited capacity version of the problem to the unlimited capacity version via an approximately efficient auction (i.e., one that maximizes the social welfare). This reduction follows from generalizable principles.

Original languageEnglish (US)
Title of host publicationProceedings of the Seventeenth Annual ACM-SIAM Symposium on Discrete Algorithms
Number of pages10
StatePublished - Feb 28 2006
EventSeventeenth Annual ACM-SIAM Symposium on Discrete Algorithms - Miami, FL, United States
Duration: Jan 22 2006Jan 24 2006


OtherSeventeenth Annual ACM-SIAM Symposium on Discrete Algorithms
Country/TerritoryUnited States
CityMiami, FL

ASJC Scopus subject areas

  • Software
  • Mathematics(all)


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