Skip to main content
Log in

Visualizing combinatorial auctions

  • Original Article
  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

We propose a novel scheme to visualize combinatorial auctions; auctions that involve the simultaneous sale of multiple items. Buyers bid on complementary sets of items, or bundles, where the utility of securing all the items in the bundle is more than the sum of the utility of the individual items. Our visualizations use concentric rings divided into arcs to visualize the bundles in an auction. The arcs’ positions and overlaps allow viewers to identify and follow bidding strategies. Properties of color, texture, and motion are used to represent different attributes of the auction, including active bundles, prices bid for each bundle, winning bids, and bidders’ interests. Keyframe animations are used to show changes in an auction over time. We demonstrate our visualization technique on a standard testbed dataset generated by researchers to evaluate combinatorial auction bid strategies, and on recent Federal Communications Commission (FCC) auctions designed to allocate wireless spectrum licenses to cell phone service providers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Bartram, L., Ware, C., Calvert, T.: Filtering and integrating visual information with motion. Inf. Vis. 1(1), 66–79 (2002)

    Google Scholar 

  2. CIE: CIE Publication No. 15, Supplement Number 2 (E-1.3.1, 1971): Official Recommendations on Uniform Color Spaces, Color-Difference Equations, and Metric Color Terms. Commission Internationale de L’Èclairge (1978)

  3. Cramton, P.: Spectrum auctions. In: Cave, M., Majumdar, S., Vogelsang, I. (eds.) Handbook of Telecommunications Economics. Elsevier, Amsterdam (2002)

    Google Scholar 

  4. Goeree, J.K., Holt, C.A., Ledyard, J.O.: An experimental comparison of flexible and tiered package bidding. http://wireless.fcc.gov/auctions/data/papersAndStudies/fcc_report_052507_final.pdf (2007)

  5. Golumbic, M.C., Ben-Arroyo Hartman, I. (eds.): Graph Theory, Combinatorics, and Algorithms: Interdisciplinary Applications. Springer, New York (2005)

    MATH  Google Scholar 

  6. Healey, C.G.: Choosing effective colours for data visualization. In: Proceedings of the 7th IEEE Visualization Conference (Vis ’96), pp. 263–270. San Francisco, California (1996)

    Chapter  Google Scholar 

  7. Healey, C.G., Enns, J.T.: Large datasets at a glance: combining textures and colors in scientific visualization. IEEE Trans. Vis. Comput. Graph. 5(2), 145–167 (1999)

    Article  Google Scholar 

  8. Huber, D.E., Healey, C.G.: Visualizing data with motion. In: Proceedings of the 16th IEEE Visualization Conference (Vis 2005), pp. 527–534, Minneapolis, Minnesota (2005)

    Google Scholar 

  9. Kosara, R., Miksch, S., Hauser, H.: Focus + context taken literally. IEEE Comput. Graph. Appl. 22(1), 22–29 (2002)

    Article  Google Scholar 

  10. Ono, C., Nishiyama, S., Horiuchi, H.: Designing a double-sided combinatorial auction system. In: Proceedings of the International Conference on Information and Knowledge Engineering 2003, pp. 445–451, Las Vegas, Nevada (2003)

    Google Scholar 

  11. Rassenti, S.J., Smith, V.L., Bulfin, R.L.: A combinatorial auction mechanism for airport time slot allocation. Bell J. Econ. 13, 402–417 (1982)

    Article  Google Scholar 

  12. Song, J., Regan, A.: Approximation algorithms for the bid construction problem in combinatorial auctions for the procurement of freight transportation contracts. Transp. Res., Part B, Methodol. 39(10), 914–933 (2005)

    Article  Google Scholar 

  13. Venn, J.: On the diagrammatic and mechanical representation of propositions and reasonings. London Edinburgh Dublin Philos. Mag. J. Sci. 9(9), 1–18 (1880)

    Google Scholar 

  14. Ware, C.: Color sequences for univariate maps: theory, experiments, and principles. IEEE Comput. Graph. Appl. 8(5), 41–49 (1988)

    Article  Google Scholar 

  15. Ware, C.: Information Visualization: Perception for Design, 2nd edn. Morgan Kaufmann, San Francisco (2004)

    Google Scholar 

  16. Wurman, P.R., Zhong, J., Cai, G.: Computing price trajectories in combinatorial auctions with proxy bidding. Electron. Commer. Res. Appl. 3(4), 329–340 (2004)

    Article  Google Scholar 

  17. Zurel, E., Nisan, N.: An efficient approximate allocation algorithm for combinatorial auctions. In: Proceedings ACM Electronic Commerce Conference, pp. 125–136, Tampa, Florida (2001)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Christopher G. Healey.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hsiao, J.PL., Healey, C.G. Visualizing combinatorial auctions. Vis Comput 27, 633–643 (2011). https://doi.org/10.1007/s00371-011-0576-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-011-0576-9

Keywords

Navigation