Proceedings of the 2018 International Conference on Advances in Social Sciences and Sustainable Development (ASSSD 2018)

The optimized strategy of urban rail transit project under Public-Private-Partnerships in China: Based on the maximum government benefit

Authors
Fei-ran Liu, Jun Liu, Xue-dong Yan
Corresponding Author
Fei-ran Liu
Available Online May 2018.
DOI
https://doi.org/10.2991/asssd-18.2018.78How to use a DOI?
Keywords
Engineering Economics; Decision Analysis; Nonlinear Programing; Urban Rail Transit; Public-Private-Partnerships; Value for Money.
Abstract
As the Public-Private-Partnership (PPP) in the domain of urban rail goes further, government policy makers care more about if any acceptable decision exists in project and maximum extent of Value for Money (VFM). However, the existing decision-making evaluation method may provide invalid and inaccurate results of the two questions. This paper proposes an optimized method which establishes a nonlinear programming model to find the decision that satisfies the private sector with reasonable payback while maximizing VFM and takes the maximum VFM value as a judge. According results of multiple independently repeated trials, the optimized method could provide valid evaluation results of the two questions under 5 scenarios of PPP project decision with the least one-time accurate rate above 76%. Thus, method pro-posed in this paper could be used as an auxiliary tool for urban rail transit project PPP decision making.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Fei-ran Liu
AU  - Jun Liu
AU  - Xue-dong Yan
PY  - 2018/05
DA  - 2018/05
TI  - The optimized strategy of urban rail transit project under Public-Private-Partnerships in China: Based on the maximum government benefit
BT  - 2018 International Conference on Advances in Social Sciences and Sustainable Development (ASSSD 2018)
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/asssd-18.2018.78
DO  - https://doi.org/10.2991/asssd-18.2018.78
ID  - Liu2018/05
ER  -