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.
Work on this paper by the second author has been supported by NSF Grant CCR-01-21555.
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Hartline, J.D., Koltun, V. (2005). Near-Optimal Pricing in Near-Linear Time. In: Dehne, F., López-Ortiz, A., Sack, JR. (eds) Algorithms and Data Structures. WADS 2005. Lecture Notes in Computer Science, vol 3608. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11534273_37
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DOI: https://doi.org/10.1007/11534273_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28101-6
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