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Fast Partial Reallocation in Combinatorial Auctions for Iterative Resource Allocation

  • Naoki Fukuta
  • Takayuki Ito
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5044)

Abstract

In this paper, we propose enhanced approximation algorithms of combinatorial auction that are suitable for the purpose of periodical reallocation of items. Our algorithms are designed to effectively reuse the last solutions to speeding up initial approximation performance. We show experimental results that show our proposed algorithms outperform existing algorithms in some aspects when the existing bids are not deleted. Also, we propose an enhanced algorithm that effectively avoids undesirable reuse of last solutions in the algorithm. This is especially effective when some existing bids are deleted from the last cycle. Furthermore, our algorithms satisfy two desirable properties: WPM for final results and Weak-WPM for intermediate results.

Keywords

Combinatorial Auction Initial Allocation Winner Determination Ubiquitous Computing Environment Winner Determination Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Naoki Fukuta
    • 1
  • Takayuki Ito
    • 2
  1. 1.Shizuoka UniversityHamamatsuJapan
  2. 2.Nagoya Institute of TechnologyGokiso-choJapan

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