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Mathematical Problems in Engineering
Volume 2012, Article ID 175912, 15 pages
Research Article

Economic Analysis on Value Chain of Taxi Fleet with Battery-Swapping Mode Using Multiobjective Genetic Algorithm

1School of Automotive Studies, Tongji University, No. 4800 Cao’an Road, Shanghai 201804, China
2The High Technology Research and Development Center, No. 1 Sanlihe Road, Beijing 100044, China
3China Automotive Engineering Research Institute Co., Ltd., Xinghuo Mansion, Fengtai District, Beijing 100071, China
4Potevio New Energy Co., Ltd., No. 6 Haidian North Second Street, Haidian District, Beijing 100080, China
5Qingdao University, No. 308 Ningxia Road, Qingdao 266071, China

Received 4 October 2012; Revised 27 November 2012; Accepted 27 November 2012

Academic Editor: Baozhen Yao

Copyright © 2012 Guobao Ning et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents an economic analysis model on value chain of taxi fleet with battery-swapping mode in a pilot city. In the model, economic benefits of charging-swapping station group, taxi company, and taxi driver in the region have been taken into consideration. Thus, the model is a multiobjective function and multiobjective genetic algorithm is used to solve this problem. According to the real data collected from the pilot city, the multiobjective genetic algorithm is tested as an effective method to solve this problem. Furthermore, the effects of price of electricity, price of battery package, life cycle of battery package, cost of battery-swapping devices and infrastructure, and driving mileage per day on the benefits of value holders are analyzed, which provide theoretical and practical reference for the deployment of electric vehicles, for the national subsidy criteria adjusment, technological innovation instruction, commercial mode selection, and infrastructure construction.