Temporary Commercial Network Programming for Beijing Olympic Games Based on Data Mining and Genetic Algorithms

Yan Chen, Jun Tian, Can Yang


This paper is committed to the optimization of the temporary commercial network programming for the 2008 Beijing Olympics. It begins with the information extraction from the Assess database of questionnaire investigations based on data mining techniques including cluster analysis and mining of association rules. Based on the discovered knowledge, we calculate customer traffics and shopping demands of the twenty commercial sites and determine the reasonable construction scales of the 20 commercial sites. In order to reach the three objectives of the programming work—meeting shopping demand, balanced distribution, and making profits—we design an optimization model based on genetic algorithms to optimize the construction scale of each site. Finally, a linear programming model is proposed for choosing the appropriate type and corresponding number of supermarket for each of the 20 sites. All the methods in this paper are innovative tools for the quantitative analysis tasks of the decision-making jobs related to the temporary commercial network of the Beijing Olympic Games.


commercial network programming, temporary supermarket, data mining, genetic algorithms.

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