• DocumentCode
    1941707
  • Title

    Automated Bidding Strategy using Genetic Algorithm for Online Auctions

  • Author

    Yu, Hongyan ; Zhang, Chenyan ; Liu, Zhongying

  • Author_Institution
    Sch. of Econ. & Manage., Tongji Univ., Shanghai
  • fYear
    2008
  • fDate
    28-29 Sept. 2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Due to the proliferation of online auctions, there is an increasing need to monitor and bid in multiple auctions in order to procure the best deal for the desired good. This paper reports on the development of a heuristic decision making framework that an agent can exploit to tackle the problem of bidding across multiple auctions with varying start and end times and with varying protocols. As the range of potential strategies is huge, we decided to use a genetic algorithm (GA) to search for effective strategies for each of the various environments that we identified. This strategy is termed the intelligent bidding strategy in the remainder of this article. Finally, we systematically evaluate the intelligent bidding strategy to highlight its operational characteristics in different scenarios and present our conclusions and further work.
  • Keywords
    decision making; electronic commerce; genetic algorithms; automated bidding strategy; genetic algorithm; heuristic decision making; intelligent bidding strategy; online auctions; Algorithm design and analysis; Autonomous agents; Decision making; Dynamic programming; Environmental economics; Genetic algorithms; Intelligent systems; Monitoring; Protocols; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Management of Information for Globalized Enterprises, 2008. AMIGE 2008. IEEE Symposium on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4244-3694-1
  • Electronic_ISBN
    978-1-4244-2972-1
  • Type

    conf

  • DOI
    10.1109/AMIGE.2008.ECP.15
  • Filename
    4721457