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A Lagrangian Heuristic for Winner Determination Problem in Combinatorial Auctions

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AI 2005: Advances in Artificial Intelligence (AI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3809))

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Abstract

We present a Lagrangian-based heuristic LAHA for the Winner Determination Problem in Combinatorial Auctions. The algorithm makes use of the market computing power by applying subgradient optimization with variable fixing. A number of different bid ordering and selection rules are used in our heuristic. Moreover, an effective local search refinement procedure is presented at the end of our algorithm. We propose a new methodology PBP to produce realistic test problems which are computationally more difficult than CATS generated benchmarks. LAHA was tested on 238 problems of 13 different distributions. Among the 146 problems for which the optimum is known, LAHA found the optimum in 91 cases and produce on average 99.2% optimal solutions for the rest. Moreover, on the other 92 hard problems for which the optimum is not known, LAHA’s solutions were on average 2% better than the solutions generated by CPLEX 8.0 in 30 minutes.

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Author information

Authors and Affiliations

  1. Dept of Industrial Engineering and Logistics Management, Hong Kong Univ of Science and Technology, Clear Water Bay, Kowloon, Hong Kong

    Andrew Lim & Jiqing Tang

  2. School of Computer Science & Engineering, South China University of Technology, GuangDong, P.R.China

    Andrew Lim

Authors
  1. Andrew Lim
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  2. Jiqing Tang
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Editor information

Editors and Affiliations

  1. Guangxi Normal University, College of CS and IT, Guilin, China, and University of Technology, Faculty of Engineering and Information Technology, Sydney, Australia

    Shichao Zhang

  2. Department of Electrical and Computer Systems Engineering, Monash University, 3800, Melbourne, Victoria, Australia

    Ray Jarvis

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© 2005 Springer-Verlag Berlin Heidelberg

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Lim, A., Tang, J. (2005). A Lagrangian Heuristic for Winner Determination Problem in Combinatorial Auctions. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_76

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  • DOI: https://doi.org/10.1007/11589990_76

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30462-3

  • Online ISBN: 978-3-540-31652-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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