Biobjective optimization for railway alignment fine-grained designs with parallel existing railways

Yan Gao,Tianlong Zhang, Caiyiyi Zhu,Shusheng Yang,Paul Schonfeld, Kai Zou, Jialing Zhang, Ying Zhu,Ping Wang,Qing He

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING(2024)

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摘要
Urban high-speed railway construction is complex due to limited land resources, high population density, and potential construction risks, especially when new tracks are parallelly aligned to operational railways. Addressing a gap in current literature on fine optimization of manual alignment in such scenarios, this paper introduces a biobjective approximate fine-grained optimization model for railway alignments (BA-FORA). Utilizing an approximate dynamic programming (ADP) method, BA-FORA effectively searches the feasible region to approach a global optimum, overcoming the dimensionality challenges inherent in standard dynamic programming (DP). This paper presents a biobjective optimization framework that takes into account both construction cost and construction risk adjacent to existing operating railways (CRAEOR), offering a method for the fine-grained design of new railways adjacent to existing railways. Finally, the proposed BA-FORA framework is applied to practical cases, demonstrating its superior optimization performance. The findings indicate that the BA-FORA model can autonomously investigate and enhance railway alignment. It generates cost-effective and low-risk solutions exceeding manual efforts, ensuring alignment constraint compliance.
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