Near-optimal pricing in near-linear time

  • Authors:
  • Jason D. Hartline;Vladlen Koltun

  • Affiliations:
  • Microsoft Research, Mountain View, CA;Computer Science Division, University of California, Berkeley, CA

  • Venue:
  • WADS'05 Proceedings of the 9th international conference on Algorithms and Data Structures
  • Year:
  • 2005

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Abstract

We present efficient approximation algorithms for a number of problems that call for computing the prices that maximize the revenue of the seller on a set of items. Algorithms for such problems enable the design of auctions and related pricing mechanisms [3]. In light of the fact that the problems we address are APX-hard in general [5], we design near-linear and near-cubic time approximation schemes under the assumption that the number of distinct items for sale is constant.