Research on the optimal selection of route design schemes for mountainous expressway based on EWM-TOPSIS coupling
Y.W. Meng, X. An, Y. Zhang, B.B. Li,
Z.S. Liu, G.Y. Qing
Pages: 259-276
Abstract:
Selecting a perfect route for a
mountainous expressway at the design stage is often challenging because
multiple feasible alternatives must be compared under competing objectives. A
quantitative evaluation framework to support mountainous expressway alignment
decision-making is proposed in this study. Eighteen indicators were
identified from 4 dimensions—project scale, technical standards, economic
benefit, and environmental benefit. Indicator weights were determined using
the entropy weight method (EWM), and the resulting weights were integrated
with the technique for order preference by similarity to an ideal solution
(TOPSIS) to establish a comprehensive alignment selection model. The relative
merit of each alternative was evaluated by comparing its distances to the
positive and negative ideal solutions. The proposed method was applied to an
actual mountainous expressway project with 4 candidate alignment schemes. The
results show that: (1) EWM reduces the influence of subjective preference in
weighting and enables a more objective indicator system, while TOPSIS
provides a transparent quantitative ranking of the alternatives; and (2)
sensitivity analysis demonstrates that the C13 scheme consistently ranks
first across ten perturbation scenarios, indicating strong robustness, and it
is therefore identified as the preferred design alternative because it is
relatively short, achieves the best technical standards, has the highest
project cost, and provides relatively good environmental benefits with moderate
house demolition requirements. The proposed EWM–TOPSIS coupling approach
represents a practical multi-attribute decision-making tool that combines
quantitative and qualitative considerations and can inform alignment scheme
selection in comparable infrastructure projects.
Keywords: mountainous expressway; alignment
schemes; entropy weight method; TOPSIS; evaluation indicators; project scale
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