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
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;
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
DOI :
10.1109/AMIGE.2008.ECP.15