Multilevel Fuzzy Decision Support Model for China-s Urban Rail Transit Planning Schemes
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.
[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.
[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.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:53050", author = "Jin-Bao Zhao and Wei Deng", title = "Multilevel Fuzzy Decision Support Model for China-s Urban Rail Transit Planning Schemes", abstract = "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", volume = "5", number = "10", pages = "1587-7", }