A decision model for high-speed railway express systems

Zhen, Lu; Gao, Jiajing; Zhang, Nianzu; Li, Haolin; Fan, Tianyi

doi:10.1016/j.cie.2023.109087

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2024

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Cited by 3 publications

References 30 publications

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High-speed railway express delivery volume forecast based on data-driven ensemble forecast approaches: The China case

Huang,

Yin,

et al. 2024

Expert Systems with Applications

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High-speed railway express delivery volume forecast based on data-driven ensemble forecast approaches: The China case

Huang,

Yin,

et al. 2024

Expert Systems with Applications

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Cargo carrying model of high-speed railway express considering transportation capacity sharing and carbon trading

Yang,

Yan,

Yang

2024

Preprint

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In order to make full use of high-speed railway (HSR) transportation capacity and facilitate the low-carbon development of transportation infrastructure, this paper examines the cargo carrying method in the context of transportation capacity sharing of HSR. With carbon trading incorporated into the profit of HSR express, a cargo carrying decision-making model with consideration of carbon trading is developed, considering constraints such as loading capacity of HSR and work ability of stations. Using genetic algorithm as the framework, a multi-loading rules genetic algorithm is designed to solve the model, considering the effect of cargo service types, origin-destination (OD) pairs, and loading priority of HSR trains. The numerical case of Xi'an-Chengdu HSR line is implemented to validate the proposed model by Gurobi solver, and the performance of different algorithm is compared. The results show that the three loading rules proposed are reasonable and the multi-loading rule genetic algorithm outperforms them. From the sensitivity analysis, it was determined that enhancing station work ability and considering train transfer can increase total profit.

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Optimization of High-Speed Rail Express Transportation Scheduling Based on Spatio-Temporal-State Network Modeling

Yang,

Xie,

Wang

2024

Applied Sciences

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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.

show abstract

A decision model for high-speed railway express systems

Cited by 3 publications

References 30 publications

High-speed railway express delivery volume forecast based on data-driven ensemble forecast approaches: The China case

High-speed railway express delivery volume forecast based on data-driven ensemble forecast approaches: The China case

Cargo carrying model of high-speed railway express considering transportation capacity sharing and carbon trading

Optimization of High-Speed Rail Express Transportation Scheduling Based on Spatio-Temporal-State Network Modeling

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