An efficient approximate algorithm for winner determination in combinatorial auctions

Yuko Sakurai, Makoto Yokoo, Koji Kamei

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

40 Citations (Scopus)

Abstract

This paper presents an approximate algorithm for the winner determination problem in combinatorial auctions. This algorithm is based on limited discrepancy search (LDS). Internet auctions have become an integral part of Electronic Commerce and can incorporate large-scale, complicated types of auctions including combinatorial auctions, where multiple items are sold simultaneously and bidders can express complementarity among these items. Although we can increase participants utilities by using combinatorial auctions, determining the optimal winners is a complicated constraint optimization problem that is shown to be NP-complete. We introduce the idea of LDS to an existing algorithm based on the IDA* algorithm, which is guaranteed to find an optimal solution. The merit of LDS is that it can avoid time-consuming re-computation of heuristic function h( ), since LDS is less sensitive to the quality of h( ). It can also limit the search efforts to promising regions. Experiments using various problem settings show that LDS can find nearoptimal solutions (better than 95%) very quickly (around 1% of the running time) compared with the existing optimal algorithm.

Original languageEnglish
Title of host publicationEC 2000 - Proceedings of the 2nd ACM Conference on Electronic Commerce
PublisherAssociation for Computing Machinery, Inc
Pages30-37
Number of pages8
ISBN (Electronic)9781581132724
DOIs
Publication statusPublished - Oct 17 2000
Event2nd ACM Conference on Electronic Commerce, EC 2000 - Minneapolis, United States
Duration: Oct 17 2000Oct 20 2000

Publication series

NameEC 2000 - Proceedings of the 2nd ACM Conference on Electronic Commerce

Conference

Conference2nd ACM Conference on Electronic Commerce, EC 2000
Country/TerritoryUnited States
CityMinneapolis
Period10/17/0010/20/00

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Software

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