Site selection of high-speed railway station : A trapezoidal fuzzy neutrosophic-based consensual group decision-making approach
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 5347-5367 |
Journal / Publication | Journal of Intelligent and Fuzzy Systems |
Volume | 40 |
Issue number | 3 |
Online published | 2 Mar 2021 |
Publication status | Published - 2021 |
Link(s)
Abstract
The need of quick and comfortable public transportation in our societies makes that many countries are planning to develop a high-speed railway network for improving their passenger transport capacity. Such a development implies among other problems how to select the location of high-speed railway station (HSRS) in each city along the line? Thus, this paper introduces an integrated approach for solving the site selection problem of HSRS, which consists of a consensus reaching process (CRP) with a group decision making (GDM) method whose inputs are trapezoidal fuzzy neutrosophic set to model experts' assessments of potential locations of HSRS. To accomplish the decision process, the inputs should be weighted and aggregated with novel trapezoidal fuzzy neutrosophic prioritized aggregation operators to reflect the priority relationship between the aggregated information. The necessity of polishing conflicts in these decisions lead then to improve the experts' agreement in the group, in our case, three consensus indexes at different levels are defined to implement the CRP. Eventually, the proposed CRP-GDM approach is put forward to solve the site selection issue of HSRS and a case of study is presented to illustrate its applications and advantages.
Research Area(s)
- consensus reaching process, High-speed railway station, prioritized aggregation operator, trapezoidal fuzzy neutrosophic set
Citation Format(s)
Site selection of high-speed railway station: A trapezoidal fuzzy neutrosophic-based consensual group decision-making approach. / Wang, Rui; Chen, Zhen-Song; Shuai, Bin et al.
In: Journal of Intelligent and Fuzzy Systems, Vol. 40, No. 3, 2021, p. 5347-5367.
In: Journal of Intelligent and Fuzzy Systems, Vol. 40, No. 3, 2021, p. 5347-5367.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review