Multilevel Fuzzy Decision Support Model for China-s Urban Rail Transit Planning Schemes
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Multilevel Fuzzy Decision Support Model for China-s Urban Rail Transit Planning Schemes

Authors: Jin-Bao Zhao, Wei Deng


This paper aims at developing a multilevel fuzzy decision support model for urban rail transit planning schemes in China under the background that China is presently experiencing an unprecedented construction of urban rail transit. In this study, an appropriate model using multilevel fuzzy comprehensive evaluation method is developed. In the decision process, the followings are considered as the influential objectives: traveler attraction, environment protection, project feasibility and operation. In addition, consistent matrix analysis method is used to determine the weights between objectives and the weights between the objectives- sub-indictors, which reduces the work caused by repeated establishment of the decision matrix on the basis of ensuring the consistency of decision matrix. The application results show that multilevel fuzzy decision model can perfectly deal with the multivariable and multilevel decision process, which is particularly useful in the resolution of multilevel decision-making problem of urban rail transit planning schemes.

Keywords: Urban rail transit, planning schemes, multilevel fuzzy decision support model, consistent matrix analysis

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[1] National Bureau of Statistics of China, China Statistical Yearbook, 2011, China Statistics Press, Beijing, 2011.
[2] J. Li and X. Wu, "Synthetic evaluation for urban rail transit line network planning scheme based on AHP-FUZZY method," Journal of Wuhan University of Technology (Transportation Science & Engineering), vol. 31, no. 2, pp. 205-207, Apr. 2007.
[3] Q. Li and F. Zhang, "Evaluation methodology of urban mass transit network project option using the fuzzy expandable engineering optimization model," China Railway Science, vol. 30, no. 6, pp. 126-131, Nov. 2009.
[4] X. Zhang and Y. Qin, "Gray relevance evaluation in urban rail transit short term construction plan," Urban Mass Transit, vol. 13, no. 9, pp. 33-37, Dec. 2010.
[5] E. E. Karsak and E. Tolga, "Fuzzy multi-criteria decision-making procedure for evaluating advanced manufacturing system investments," International Journal of Production Economics, vol. 69, no. 1, pp. 49-64, Jan. 2001.
[6] G. Sheng, D. Rong, H. Guo, Y. Zhou, and Z. He, "Fuzzy comprehensive evaluation on the quality of different mixed feeds for fattening lambs by using in vitro method, " Livestock Science, vol. 115, no. 2, pp. 137-143, Jun. 2008.
[7] K. C. Lama, X. Ning, and H. Gao, "The fuzzy GA-based multi-objective financial decision support model for Chinese state-owned construction firms," Automation in Construction, vol.18, no.4, pp. 402-414, Dec. 2009.
[8] G. Zheng, Y. Jing, H. Huang, and Y. Gao, "Application of improved grey relational projection method to evaluate sustainable building envelope performance, "Applied Energy, vol. 87, no. 2, pp. 710-720, Feb. 2010.
[9] Y. Ye, L. Ke, and D. Huang, The System Integrated Evaluation Technology and Its Application, Metallurgical Industry Press, Beijing, 2006.
[10] T. L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New York, 1980.
[11] L. Li and L .Shen, "An improved multilevel fuzzy comprehensive evaluation algorithm for security performance," The Journal of China Universities of Posts and Telecommunications, vol. 13, no. 4, pp.48-53, Dec. 2006.