Dataset Information

Logistics hub location for high-speed rail freight transport with road-rail intermodal transport network.

ABSTRACT: In this paper, we propose a new freight mode to describe how the designed HSR freight train serve for express delivery. We introduce the functions of the hubs and design the hybrid hub-and-spoke network of road-rail intermodal transportation from the perspective of planners, which features as single allocation rule and configures varying levels of hubs. The problem is accurately described by a mixed integer programming model with the objective to minimize total construction cost and total operation cost. We develop a hybrid heuristic algorithm based on a greedy strategy to obtain the levels of hubs, customer allocation and cargo routing. Taking the example of HSR freight network consisting of 50 cities in China, numerical experiments are conducted on the basis of forecasting data from the real-life express market to obtain the hub location schemes. The validity of the model and the performance of the algorithm are verified.

SUBMITTER: Li S

PROVIDER: S-EPMC10335689 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Logistics hub location for high-speed rail freight transport with road-rail intermodal transport network.

Li Siyu S Lang Maoxiang M Chen Xinghan X Li Shiqi S Liu Wenqian W Tang Weilin W

PloS one 20230711 7

In this paper, we propose a new freight mode to describe how the designed HSR freight train serve for express delivery. We introduce the functions of the hubs and design the hybrid hub-and-spoke network of road-rail intermodal transportation from the perspective of planners, which features as single allocation rule and configures varying levels of hubs. The problem is accurately described by a mixed integer programming model with the objective to minimize total construction cost and total operat ...[more]

PMID: 37432948

Similar Datasets

Project description:This data article describes a dataset on European road freight traffic. The dataset includes truck traffic flows between 1675 regions all over Europe. In addition to the road freight flows in tons as well as number of vehicles, the dataset also contains the shortest path between the respective regions on the European highway network (E-roads). Fifteen columns provide the following information for each pair of regions: (1) ID origin region, (2) name origin region, (3) ID destination region, (4) name destination region, (5) path in the E-road network, (6) distance from origin region to the E-road network, (7) distance within the E-road network, (8) distance from the E-road network to the destination region, (9) total distance, (10) road freight flow in tons for 2010, (11) road freight flow in tons for 2019, (12) road freight flow in tons for 2030, (13) truck traffic flow in number of vehicles for 2010, (14) truck traffic flow in number of vehicles for 2019, (15) truck traffic flow in number of vehicles for 2030. In addition, a table of nodes and a table of edges of the modelled E-road network is available. Finally, a list with supplementary information on the regions under consideration is given. In 2010, the ETISplus project collected Europe-wide freight volumes from various EU sources as well as from the EU countries and calibrated the resulting origin-destination matrices with measured traffic flows. For the dataset described here, the road freight volume was updated using Eurostat data and a forecast up to 2030 was added. The freight volume was converted into vehicles travelling. Subsequently, the highway network relevant for trucks was extracted from the ETISplus project and manually updated with the current E-road network. Finally, each origin-destination freight volume was allocated to the network using Dijkstra's algorithm. This provides a synthetically generated road freight traffic volume for each road section. The generated data provide an extremely relevant basis for the design of future road infrastructure in Europe, for example hydrogen refuelling stations or charging stations for electric trucks. Thus, the data are not only relevant for traffic science studies, but also of high importance for planners in practice.

Dataset Information

Logistics hub location for high-speed rail freight transport with road-rail intermodal transport network.

Publications

Logistics hub location for high-speed rail freight transport with road-rail intermodal transport network.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets