Genetic Algorithm for Forming Buyer Coalition with Bundles of Items in E-Marketplaces

  • Anon SukstrienwongEmail author
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 70)


The benefits of buyer coalitions are well-known for electronic marketplaces. However, a few existing buyer coalition schemes over the Internet have focused on forming a buyer coalition with bundles of items. This paper presents an algorithm to form a buyer coalition with bundles of items by using genetic algorithms (GAs). The algorithm called GAGroupBuying finds the best disjoint subsets of all buyers based on the total utility which addresses the situation where a whole group of buyers can be partitioned into smaller sub-groups to obtain more utility than they could accomplish in the whole group. The proposed algorithm is compared with a previous algorithm called GroupPackageString as shown by Boongasame and Sukstrienwong (Emerging Intelligent Computing Technology and Applications, pp. 674–685, 2009). The results of GAGroupBuying simulation are found to be satisfactory with the total discount of a buyer coalition.


Genetic algorithm Buyer coalition Bundles of items Coalition structure 


  1. 1.
    Boongasame, L., Sukstrienwong, A.: Buyer coalitions with bundles of items by using genetic algorithm. In: Emerging Intelligent Computing Technology and Applications, pp. 674–685. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  2. 2.
    Chang, Y., Li, C., Smith, J.R.: Searching dynamically bundled goods with pairwise relations. In: Proceedings of ACM Electronic Commerce, pp. 135–143 (2003) Google Scholar
  3. 3.
    Li, C., Sycara, K.: Algorithm for combinatorial coalition formation and payoff diversion in an electronic marketplace. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 120–127 (2002) Google Scholar
  4. 4.
    He, L., Ioerger, T.: Combining bundle search with buyer coalition formation in Electronic Markets: A distributed approach through explicit negotiation. Electron. Commerce Res. Appl. 4(4), 329–344 (2005) CrossRefGoogle Scholar
  5. 5.
    Chen, D., Jeng, B., Lee, W., Chuang, C.: An agent-based model for consumer-to-business electronic commerce. Expert Syst. Appl. 34(1), 469–481 (2008) CrossRefGoogle Scholar
  6. 6.
    Ito, T., Hiroyuki, O., Toramatsu, S.: A group buy protocol based on coalition formation for agent-mediated e-commerce. IJCIS 3(1), 11–20 (2002) Google Scholar
  7. 7.
    Tsvetovat, M., Sycara, K.P., Chen, Y., Ying, J.: Customer coalitions in electronic markets. In: Dignum, F., Cortés, U. (eds.) AMEC III. LNAI, vol. 2003, pp. 121–138 (2001) Google Scholar
  8. 8.
    Yamamoto, J., Sycara, K.: A stable and efficient buyer coalition formation scheme for e-marketplaces. In: Proceedings of the 5th International Conference on Autonomous Agents, Montreal, Quebec, Canada, pp. 576–583 (2001) Google Scholar
  9. 9.
    Hyodo, M., Matsuo, T., Ito, T.: An optimal coalition formation among buyer agents based on a genetic algorithm. In: 16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE’03), Laughborough, UK, pp. 759–767 (2003) Google Scholar
  10. 10.
    Gürle, U., Öztop, S., Şen, A.: Optimal bundle formation and pricing of two products with limited stock. Int. J. Product. Econ. 118(2), 442–462 (2009) CrossRefGoogle Scholar
  11. 11.
    Koza, J.: Genetic Programming on the Programming of Computers by Means of Natural Selection. The MIT Press, Cambridge (1992) zbMATHGoogle Scholar
  12. 12.
    Sandholm, T.W., Larson, K.S., Andersson, M.R., Shehory, O., Tohme, F.: Coalition structure generation with worst case guarantees. Artif. Intell. 111, 209–238 (1999) MathSciNetzbMATHCrossRefGoogle Scholar
  13. 13.
    Sukstrienwong, A.: Buyer formation with bundle of items in e-marketplaces by genetic algorithm. In: Lecture Notes in Engineering and Computer Science: Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010, Hong Kong, 17–19 March 2010, pp. 158–162 (2010) Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Information Technology Department, School of Science and TechnologyBangkok UniversityBangkokThailand

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