Optimization of High-Speed Rail Express Transportation Scheduling Based on Spatio-Temporal-State Network Modeling
Source abstract
Abstract
High-speed rail express is gradually gaining attention due to its low cost and high on-time performance. This paper studied the optimization of high-speed rail express transportation modes considering passenger capacity loss. A spatio-temporal network was constructed that includes the fixed passenger train schedule and the high-speed rail express transportation status. Based on this network, an optimization model for transportation schemes considering passenger capacity loss with non-splittable freight flows was developed. The model aims to minimize passenger loss and maximize net revenue from express transportation while comprehensively considering practical constraints such as transfer, loading and unloading, and carrying capacity. The Gurobi optimization solver was used to solve numerical cases, and the optimization results and solution effectiveness were comparatively analyzed under scenarios of sufficient and insufficient capacity.
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Research context
OpenAlex topics: Cognitive Computing and Networks
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Affiliations
Research Institute of Highway Ministry of Transport, No. 8 Xitucheng Rd, Beijing 100088, China
Logistics School, Beijing Wuzi University, No. 321 Fuhe Street, Beijing 101149, China
School of Traffic and Transportation, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Beijing 100044, China
References (19)
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