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New Trends in Agent-Based Complex Automated Negotiations pp 81–98Cite as

Matchmaking in Multi-attribute Auctions using a Genetic Algorithm and a Particle Swarm Approach

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 383))

Abstract

An electronic market platform usually requires buyers and sellers to exchange offers-to-buy and offers-to-sell. The goal of this exchange is to reach an agreement on the suitability of closing transactions between buyers and sellers. This paper investigates multi-attribute auctions, and in particular the matchmaking of multiple buyers and sellers based on five attributes. The proposed approaches are based on a Genetic Algorithm (GA) and a Particle Swarm Optimization (PSO) approach to match buyers with sellers based on five attributes as closely as possible. Our approaches are compared with an optimal assignment algorithm called the Munkres algorithm, as well as with a simple random approach. Measurements are performed to quantify the overall match score and the execution time. Both, the GA as well as the PSO approach show good performance, as even though not being optimal algorithms, they yield a high match score when matching the buyers with the sellers. Furthermore, both algorithms take less time to execute than the Munkres algorithm, and therefore, are very attractive for matchmaking in the electronic market place, especially in cases where large numbers of buyers and sellers need to be matched efficiently.

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Author information

Authors and Affiliations

  1. Department of Computer Science, North Dakota State University, Fargo, North Dakota, U.S.A.

    Simone A. Ludwig

  2. Department of Computer Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada

    Thomas Schoene

Authors
  1. Simone A. Ludwig
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  2. Thomas Schoene
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Correspondence to Simone A. Ludwig .

Editor information

Editors and Affiliations

  1. Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Nagoya, Showa, 466-8555, Japan

    Takayuki Ito

  2. School of Information Technology &, Computer Science, University of Wollongong, Northfields Avenue, Wollongong, 2522, New South Wales, Australia

    Minjie Zhang

  3. , School of Electronics and Computer Scien, University of Southampton, Southampton, SO17 1BJ, United Kingdom

    Valentin Robu

  4. Dept. Computer Studies, Loughborough University, Loughborough, Leics., LE11 3TU, United Kingdom

    Shaheen Fatima

  5. School of Engineering, Dept. of Mechanical Systems Engineering, Yamagata University, Jonan 4-3-16, Yonezawa, 992-8510, Japan

    Tokuro Matsuo

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© 2012 Springer-Verlag Berlin Heidelberg

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Ludwig, S.A., Schoene, T. (2012). Matchmaking in Multi-attribute Auctions using a Genetic Algorithm and a Particle Swarm Approach. In: Ito, T., Zhang, M., Robu, V., Fatima, S., Matsuo, T. (eds) New Trends in Agent-Based Complex Automated Negotiations. Studies in Computational Intelligence, vol 383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24696-8_5

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  • DOI: https://doi.org/10.1007/978-3-642-24696-8_5

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24695-1

  • Online ISBN: 978-3-642-24696-8

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