High-Speed Rail Station Location Optimization Using Customized Utility Functions

High-speed rail station location (HSR-SL) is a complex problem with multiple conflicting factors, such as local transportation network connectivity, regional accessibility, downtown proximity, and feasibility. The proposed novel methodology quantified these factors using customized nonlinear, linear, or integer utility functions. Suitable distance decay models to quantify the local transport access to and from existing bus stops, train stations, and downtown proximity; a gravity model for potential regional accessibility to the residential population or workforce; linear models for connectivity with the existing public transit routes and normalized land cost; and a binary model with a threshold value for geographical feasibility in terms of environmental sensitivity were developed. These models were evaluated using a geospatial and network analysis-based approach, and the overall nonlinear HSR-SL problem was optimized using the particle swarm optimization algorithm. The results of a real-world study area in downtown Tokyo, Japan, revealed that customized utility functions for various factors reduced the possibility of over- or underestimation and the selection of suboptimal SLs. The proposed method improved estimation of the land cost feasibility, access to transfer points, and connectivity by 100%, 185%, and 222%, respectively, for the given case study. It was most sensitive to connectivity and proximity to the downtown area, followed by location cost, transportation access, and population or workforce potential accessibility.