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Ascending Combinatorial Auctions with Allocation Constraints: On Game Theoretical and Computational Properties of Generic Pricing Rules

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  • Ioannis Petrakis

    (Decision Sciences and Systems, Department of Informatics, Technische Universität München, 80333 Munich, Germany)

  • Georg Ziegler

    (Decision Sciences and Systems, Department of Informatics, Technische Universität München, 80333 Munich, Germany)

  • Martin Bichler

    (Decision Sciences and Systems, Department of Informatics, Technische Universität München, 80333 Munich, Germany)

Abstract

Combinatorial auctions are used in a variety of application domains, such as transportation or industrial procurement, using a variety of bidding languages and different allocation constraints. This flexibility in the bidding languages and the allocation constraints is essential in these domains but has not been considered in the theoretical literature so far. In this paper, we analyze different pricing rules for ascending combinatorial auctions that allow for such flexibility: winning levels and deadness levels. We determine the computational complexity of these pricing rules and show that deadness levels actually satisfy an ex post equilibrium, whereas winning levels do not allow for a strong game theoretical solution concept. We investigate the relationship of deadness levels and the simple price update rules used in efficient ascending combinatorial auction formats. We show that ascending combinatorial auctions with deadness level pricing rules maintain a strong game theoretical solution concept and reduce the number of bids and rounds required at the expense of higher computational effort. The calculation of exact deadness levels is a \documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland,xspace}\usepackage{amsmath,amsxtra}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document}$\Pi_2^P$\end{document} -complete problem. Nevertheless, numerical experiments show that for mid-sized auctions this is a feasible approach. The paper provides a foundation for allocation constraints in combinatorial auctions and a theoretical framework for recent Information Systems contributions in this field.

Suggested Citation

  • Ioannis Petrakis & Georg Ziegler & Martin Bichler, 2013. "Ascending Combinatorial Auctions with Allocation Constraints: On Game Theoretical and Computational Properties of Generic Pricing Rules," Information Systems Research, INFORMS, vol. 24(3), pages 768-786, September.
  • Handle: RePEc:inm:orisre:v:24:y:2013:i:3:p:768-786
    DOI: 10.1287/isre.1120.0452
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    Cited by:

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    3. Bart Vangerven & Dries R. Goossens & Frits C. R. Spieksma, 2021. "Using Feedback to Mitigate Coordination and Threshold Problems in Iterative Combinatorial Auctions," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(2), pages 113-127, April.
    4. Martin Bichler & Johannes Knörr & Felipe Maldonado, 2023. "Pricing in Nonconvex Markets: How to Price Electricity in the Presence of Demand Response," Information Systems Research, INFORMS, vol. 34(2), pages 652-675, June.
    5. Martin Bichler & Zhen Hao & Gediminas Adomavicius, 2017. "Coalition-Based Pricing in Ascending Combinatorial Auctions," Information Systems Research, INFORMS, vol. 28(1), pages 159-179, March.
    6. Bichler, Martin & Goeree, Jacob K., 2017. "Frontiers in spectrum auction design," International Journal of Industrial Organization, Elsevier, vol. 50(C), pages 372-391.
    7. Martin Bichler & Vladimir Fux & Jacob Goeree, 2018. "A Matter of Equality: Linear Pricing in Combinatorial Exchanges," Information Systems Research, INFORMS, vol. 29(4), pages 1024-1043, December.
    8. Gediminas Adomavicius & Alok Gupta & Mochen Yang, 2022. "Bidder Support in Multi-item Multi-unit Continuous Combinatorial Auctions: A Unifying Theoretical Framework," Information Systems Research, INFORMS, vol. 33(4), pages 1174-1195, December.

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