Stochastic optimization model for determining support system parameters of a subway station

作者：

Highlights：

• Precise estimation of the support system parameters of a subway station.

• Developing a stochastic multi-objective optimization model using NSGA-III.

• Estimating the risk of uncertainties in c and ϕ by CVaR.

• Ranking all optimal solutions using The ELECTRE model.

摘要

•Precise estimation of the support system parameters of a subway station.•Developing a stochastic multi-objective optimization model using NSGA-III.•Estimating the risk of uncertainties in c and ϕ by CVaR.•Ranking all optimal solutions using The ELECTRE model.

论文关键词：Subway station design,Finite Element Method,Artificial neural network,Conditional Value at Risk,NSGA-III,ELECTRE

论文评审过程：Received 22 March 2021, Revised 21 April 2022, Accepted 3 May 2022, Available online 7 May 2022, Version of Record 20 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117509