Affiliations: [a] Economics and Management School, Wuhan University, Wuhan, Hubei, China
| [b] School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, China
| [c] Business School, Zhengzhou University of Aeronautics, Zhengzhou, Henan, China
Correspondence:
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Corresponding author. Ma Gang, Economics and Management School, Wuhan University, Wuhan, Hubei, 430000, China. E-mail: magang@whu.edu.cn.
Abstract: With the development of “Internet+”, online auction platforms of used cars have emerged a lot. As a typical representative of the continuous purchase environment, online sequential auction of used cars faces many uncertainties, including uncertain revenue and risk. To describe them, adopting fuzzy theory to create mean-variance model to estimate the revenue and risk is showed in this paper. Moreover, three types of sellers, aggressive, conservative and rational sellers are analyzed respectively, and strategy models are built, where the multi-criteria optimal function for the latter one is adapted Cobb-Douglas production function. Then, a genetic algorithm based on fuzzy simulation is proposed through integrating the fuzzy simulation and 0-1 genetic algorithm, which can solve the models validly. Lastly, the practical example from Guazi website shows the optimal strategies derived by models can meet sellers’ demands, especially goals of both higher revenue and lower risk for rational sellers, which proves practicability of the model and validity of algorithm.
