Software Environment for Market Balancing Mechanisms Development, and Its Application to Solving More General Problems in Parallel Way

  • Mariusz Kamola
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7133)

Abstract

A new software that supports research on algorithms for resource allocation in multi-commodity markets is presented. Thanks to a much more general data model used, and possibility of plugging in external optimization engines, various solvers can be used to extend the functionality of the platform. The software functionality is focused on supporting researchers in the algorithm engineering process, facilitating e.g. analysis and comparison of market strategies. An example application of the software to travelling salesman problem, solved by many agents, is presented.

Keywords

Resource Allocation Social Network Analysis Travel Salesman Problem Travel Salesman Problem Software Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    Gavaghan, M.: GPS Receivers and Geocaching: Vincenty’s Formula — a section of the web page, http://www.gavaghan.org/blog/category/codeproject (accessed March 30, 2010)
  2. [2]
    Kacprzak, P., Kaleta, M., Pałka, P., Smolira, K., Toczyłowski, E., Traczyk, T.: M3: Open Multi-commodity Market Data Model for Network Systems. In: Proceedings of the XVI International Conference on System Science, Wrocław (2007)Google Scholar
  3. [3]
    Kacprzak, P., Kaleta, M., Pałka, P., Smolira, K., Toczyłowski, E., Traczyk, T.: Communication model for M3— Open Multi-commodity Market Data Model. In: Proceedings of TPD 2007 Polish Conference, Poznań (2007)Google Scholar
  4. [4]
    Kacprzak, P., Kaleta, M., Pałka, P., Smolira, K., Toczyłowski, E., Traczyk, T.: Application of open multi-commodity market data model on the communication bandwidth market. J. Telecommunications and Information Technology 4, 45–50 (2007)Google Scholar
  5. [5]
    Karpowicz, M., Malinowski, K.: Network flow optimization with rational agents. NASK internal report (2009)Google Scholar
  6. [6]
    Pałka, P., Kołtyś, K., Toczyłowski, E., Żółtowska, I.: Model for Balancing Aggregated Communication Bandwidth Resources. J. Telecommunications and Information Technology 3, 43–49 (2009)Google Scholar
  7. [7]
    Stańczuk, W., Pałka, P., Lubacz, J., Toczyłowski, E.: Parametric pricing rule in bandwidth trade. In: Proceedings of 8th International Conference on Decision Support for Telecommunications and Information Society DIST 2009, Coimbra (2009)Google Scholar
  8. [8]
    XSLT transformation “toAmpl-BCBTxsl” Documentation contained in archive available in Tools/XSLT files section of the web page, http://www.openm3.org (accessed March 30, 2010)
  9. [9]
    Google Web Toolkit Overview, http://code.google.com/webtoolkit/overview.html (accessed March 30, 2010)
  10. [10]
    Ausiello, G., Leonardi, S., Marchetti-Spaccamela, A.: On Salesmen, Repairmen, Spiders, and Other Traveling Agents. In: Bongiovanni, G., Petreschi, R., Gambosi, G. (eds.) CIAC 2000. LNCS, vol. 1767, pp. 1–16. Springer, Heidelberg (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mariusz Kamola
    • 1
    • 2
  1. 1.Institute of Control and Computation EngineeringWarsaw University of TechnologyPoland
  2. 2.NASK (Research and Academic Computer Network)Poland

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