Symmetry-Based Urban Rail Transit Network Planning Using Two-Stage Robust Optimization DOI Open Access
Zhaoguo Huang, Changxi Ma

Symmetry, Journal Year: 2024, Volume and Issue: 16(9), P. 1149 - 1149

Published: Sept. 4, 2024

To address the symmetry-related resilience issues of stations and lines in urban rail transit networks, we propose a two-stage robust optimization-based approach for network planning. In this context, is conceptualized as ability to maintain its operational symmetry under normal disruptive conditions. Firstly, used passenger flow distributions decision variables construct symmetry-based planning model, aiming simultaneously minimize total cost operating time while preserving functional symmetry. Secondly, designed hybrid evolutionary algorithm with chromosomes having two-layer encoding structure, where Niched Pareto Genetic Algorithm served main algorithmic framework, Large Neighborhood Search mechanism was optimize connectivity gene layer individuals, ensuring connectivity. Finally, conducted computational verification on randomly generated instances confirm effectiveness model algorithm. The experimental results demonstrated that our method could find two sets optimal solutions preference preference, thereby damaged conditions, well reducing time. This effectively improved overall efficiency network. Our converged satisfactory objective values early iterations, exhibiting strong search optimization performance solving model.

Language: Английский

Time-dependent effect of advanced driver assistance systems on driver behavior based on connected vehicle data DOI
Yuzhi Chen, Yuanchang Xie, Chen Wang

et al.

Analytic Methods in Accident Research, Journal Year: 2025, Volume and Issue: unknown, P. 100370 - 100370

Published: Jan. 1, 2025

Language: Английский

Citations

0

Symmetry-Based Urban Rail Transit Network Planning Using Two-Stage Robust Optimization DOI Open Access
Zhaoguo Huang, Changxi Ma

Symmetry, Journal Year: 2024, Volume and Issue: 16(9), P. 1149 - 1149

Published: Sept. 4, 2024

To address the symmetry-related resilience issues of stations and lines in urban rail transit networks, we propose a two-stage robust optimization-based approach for network planning. In this context, is conceptualized as ability to maintain its operational symmetry under normal disruptive conditions. Firstly, used passenger flow distributions decision variables construct symmetry-based planning model, aiming simultaneously minimize total cost operating time while preserving functional symmetry. Secondly, designed hybrid evolutionary algorithm with chromosomes having two-layer encoding structure, where Niched Pareto Genetic Algorithm served main algorithmic framework, Large Neighborhood Search mechanism was optimize connectivity gene layer individuals, ensuring connectivity. Finally, conducted computational verification on randomly generated instances confirm effectiveness model algorithm. The experimental results demonstrated that our method could find two sets optimal solutions preference preference, thereby damaged conditions, well reducing time. This effectively improved overall efficiency network. Our converged satisfactory objective values early iterations, exhibiting strong search optimization performance solving model.

Language: Английский

Citations

0