IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v69y2023i4p2217-2238.html
   My bibliography  Save this article

Taming the Communication and Computation Complexity of Combinatorial Auctions: The FUEL Bid Language

Author

Listed:
  • Martin Bichler

    (Department of Informatics, Technical University of Munich, 85748 Munich, Germany)

  • Paul Milgrom

    (Department of Economics, Stanford University, Stanford, California 94305)

  • Gregor Schwarz

    (Department of Informatics, Technical University of Munich, 85748 Munich, Germany)

Abstract

Combinatorial auctions have found widespread application for allocating multiple items in the presence of complex bidder preferences. The enumerative exclusive OR (XOR) bid language is the de facto standard bid language for spectrum auctions and other applications, despite the difficulties, in larger auctions, of enumerating all the relevant packages or solving the resulting NP-hard winner determination problem. We introduce the flexible use and efficient licensing (FUEL) bid language, which was proposed for radio spectrum auctions to ease both communications and computations compared with XOR-based auctions. We model the resulting allocation problem as an integer program, discuss computational complexity, and conduct an extensive set of computational experiments, showing that the winner determination problem of the FUEL bid language can be solved reliably for large realistic-sized problem instances in less than half an hour on average. In contrast, auctions with an XOR bid language quickly become intractable even for much smaller problem sizes. We compare a sealed-bid FUEL auction to a sealed-bid auction with an XOR bid language and to a simultaneous clock auction. The sealed-bid auction with an XOR bid language incurs significant welfare losses because of the missing bids problem and computational hardness, the simultaneous clock auction leads to a substantially lower efficiency than FUEL because of the exposure problem.

Suggested Citation

  • Martin Bichler & Paul Milgrom & Gregor Schwarz, 2023. "Taming the Communication and Computation Complexity of Combinatorial Auctions: The FUEL Bid Language," Management Science, INFORMS, vol. 69(4), pages 2217-2238, April.
  • Handle: RePEc:inm:ormnsc:v:69:y:2023:i:4:p:2217-2238
    DOI: 10.1287/mnsc.2022.4465
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2022.4465
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.2022.4465?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Paul Milgrom, 2009. "Assignment Messages and Exchanges," American Economic Journal: Microeconomics, American Economic Association, vol. 1(2), pages 95-113, August.
    2. Frank Kelly & Richard Steinberg, 2000. "A Combinatorial Auction with Multiple Winners for Universal Service," Management Science, INFORMS, vol. 46(4), pages 586-596, April.
    3. Iftekhar, M.S. & Tisdell, J.G., 2012. "Comparison of simultaneous and combinatorial auction designs in fisheries quota market," Marine Policy, Elsevier, vol. 36(2), pages 446-453.
    4. Bichler, Martin & Paulsen, Per, 2018. "A principal-agent model of bidding firms in multi-unit auctions," Games and Economic Behavior, Elsevier, vol. 111(C), pages 20-40.
    5. Peter Cramton, 2017. "Electricity market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 589-612.
    6. Andor Goetzendorff & Martin Bichler & Pasha Shabalin & Robert W. Day, 2015. "Compact Bid Languages and Core Pricing in Large Multi-item Auctions," Management Science, INFORMS, vol. 61(7), pages 1684-1703, July.
    7. Lehmann, Benny & Lehmann, Daniel & Nisan, Noam, 2006. "Combinatorial auctions with decreasing marginal utilities," Games and Economic Behavior, Elsevier, vol. 55(2), pages 270-296, May.
    8. Bichler, Martin & Schneider, Stefan & Guler, Kemal & Sayal, Mehmet, 2011. "Compact bidding languages and supplier selection for markets with economies of scale and scope," European Journal of Operational Research, Elsevier, vol. 214(1), pages 67-77, October.
    9. Robert W. Day & S. Raghavan, 2007. "Fair Payments for Efficient Allocations in Public Sector Combinatorial Auctions," Management Science, INFORMS, vol. 53(9), pages 1389-1406, September.
    10. Milgrom,Paul, 2004. "Putting Auction Theory to Work," Cambridge Books, Cambridge University Press, number 9780521536721.
    11. Martin Bichler & Pasha Shabalin & Georg Ziegler, 2013. "Efficiency with Linear Prices? A Game-Theoretical and Computational Analysis of the Combinatorial Clock Auction," Information Systems Research, INFORMS, vol. 24(2), pages 394-417, June.
    12. Tobias Scheffel & Georg Ziegler & Martin Bichler, 2012. "On the impact of package selection in combinatorial auctions: an experimental study in the context of spectrum auction design," Experimental Economics, Springer;Economic Science Association, vol. 15(4), pages 667-692, December.
    13. 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.
    14. Lawrence M. Ausubel & Oleg V. Baranov, 2014. "Market Design and the Evolution of the Combinatorial Clock Auction," American Economic Review, American Economic Association, vol. 104(5), pages 446-451, May.
    15. Robert W. Day & Peter Cramton, 2012. "Quadratic Core-Selecting Payment Rules for Combinatorial Auctions," Operations Research, INFORMS, vol. 60(3), pages 588-603, June.
    16. Bichler, Martin & Goeree, Jacob & Mayer, Stefan & Shabalin, Pasha, 2014. "Spectrum auction design: Simple auctions for complex sales," Telecommunications Policy, Elsevier, vol. 38(7), pages 613-622.
    17. Peter Cramton & Yoav Shoham & Richard Steinberg (ed.), 2006. "Combinatorial Auctions," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262033429, December.
    18. Nisan, Noam & Segal, Ilya, 2006. "The communication requirements of efficient allocations and supporting prices," Journal of Economic Theory, Elsevier, vol. 129(1), pages 192-224, July.
    19. Jonathan Levin & Andrzej Skrzypacz, 2016. "Properties of the Combinatorial Clock Auction," American Economic Review, American Economic Association, vol. 106(9), pages 2528-2551, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Scott Duke Kominers & Alexander Teytelboym & Vincent P Crawford, 2017. "An invitation to market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 541-571.
    2. Alexander Teytelboym & Shengwu Li & Scott Duke Kominers & Mohammad Akbarpour & Piotr Dworczak, 2021. "Discovering Auctions: Contributions of Paul Milgrom and Robert Wilson," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(3), pages 709-750, July.
    3. Andor Goetzendorff & Martin Bichler & Pasha Shabalin & Robert W. Day, 2015. "Compact Bid Languages and Core Pricing in Large Multi-item Auctions," Management Science, INFORMS, vol. 61(7), pages 1684-1703, July.
    4. Pallab Sanyal, 2016. "Characteristics and Economic Consequences of Jump Bids in Combinatorial Auctions," Information Systems Research, INFORMS, vol. 27(2), pages 347-364, June.
    5. Kazumori, Eiichiro & Belch, Yaakov, 2019. "t-Tree: The Tokyo toolbox for large-scale combinatorial auction experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 24(C).
    6. Eric Budish & Judd B. Kessler, 2022. "Can Market Participants Report Their Preferences Accurately (Enough)?," Management Science, INFORMS, vol. 68(2), pages 1107-1130, February.
    7. Committee, Nobel Prize, 2020. "Improvements to auction theory and inventions of new auction formats," Nobel Prize in Economics documents 2020-2, Nobel Prize Committee.
    8. Christian Kroemer & Martin Bichler & Andor Goetzendorff, 2016. "(Un)expected Bidder Behavior in Spectrum Auctions: About Inconsistent Bidding and Its Impact on Efficiency in the Combinatorial Clock Auction," Group Decision and Negotiation, Springer, vol. 25(1), pages 31-63, January.
    9. 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.
    10. Lamprirni Zarpala & Dimitris Voliotis, 2022. "A core-selecting auction for portfolio's packages," Papers 2206.11516, arXiv.org, revised Feb 2024.
    11. Mochon, Asuncion & Saez, Yago, 2017. "A review of radio spectrum combinatorial clock auctions," Telecommunications Policy, Elsevier, vol. 41(5), pages 303-324.
    12. Martin Bichler & Pasha Shabalin & Jürgen Wolf, 2013. "Do core-selecting Combinatorial Clock Auctions always lead to high efficiency? An experimental analysis of spectrum auction designs," Experimental Economics, Springer;Economic Science Association, vol. 16(4), pages 511-545, December.
    13. Blumrosen, Liad & Nisan, Noam, 2010. "Informational limitations of ascending combinatorial auctions," Journal of Economic Theory, Elsevier, vol. 145(3), pages 1203-1223, May.
    14. 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.
    15. Blumrosen, Liad & Solan, Eilon, 2023. "Selling spectrum in the presence of shared networks: The case of the Israeli 5G auction," Telecommunications Policy, Elsevier, vol. 47(2).
    16. Bichler, Martin & Goeree, Jacob K., 2017. "Frontiers in spectrum auction design," International Journal of Industrial Organization, Elsevier, vol. 50(C), pages 372-391.
    17. Jeremy Bulow & Jonathan Levin & Paul Milgrom, 2009. "Winning Play in Spectrum Auctions," NBER Working Papers 14765, National Bureau of Economic Research, Inc.
    18. 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.
    19. Benedikt Bünz & Benjamin Lubin & Sven Seuken, 2022. "Designing Core-Selecting Payment Rules: A Computational Search Approach," Information Systems Research, INFORMS, vol. 33(4), pages 1157-1173, December.
    20. Aytek Erdil & Paul Klemperer, 2010. "A New Payment Rule for Core-Selecting Package Auctions," Journal of the European Economic Association, MIT Press, vol. 8(2-3), pages 537-547, 04-05.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:69:y:2023:i:4:p:2217-2238. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.