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This paper envisions a multimodal passenger-and-package sharing (PPS) network for urban logistics integrating metro, taxi, and truck. A hub-and-spoke structure is designed including hubs located at metro stations and service stores connected to the hubs. Packages are transported by metro on backbone links between the hubs and are carried by taxis or trucks between service stores and hubs, depending on the unit costs of these two modes and capacity constraint of the taxi. A mixed integer linear programming model for hub location problems—fusing the multiassignment p-hub median problem without capacity constraints and the capacitated multiassignment p-hub covering problem—is formulated to optimize the multimodal PPS network. The model is implemented based on the real-world data in Shanghai (China) under a series of scenarios to evaluate the network performance from two perspectives: the number of hubs and the proportion of taxi drivers who are willing to carry packages. The scenarios show that with increased number of hubs, the spatial distribution of hubs disperses from the city center to peripheral areas and more areas can be serviced by taxis. There is, however, a trade-off between the operation cost saved by taxis and the establishment cost of an extra hub. The analysis also presents that if the proportion of taxis willing to carry packages associates with the incentive payments to taxi drivers, an optimal value of incentives exists, by balancing the operation costs of taxis and trucks. [ABSTRACT FROM AUTHOR]

• A satellite terminal is integrated into the inter-terminal transportation (ITT) • A time–space network flow model is developed to minimize the ITT cost. • Two approaches are proposed to reduce the solution space of the model. • The influence of the satellite terminal on the Yangshan Port, Shanghai is evaluated. Offshore ports, which are located on islands or away from the hinterland, are usually connected with the hinterland via bridges for truck transportation. With the rapid growth of port throughput, the bridges are likely to become a bottleneck restricting the development of port business. Inland container depots (ICD) have been introduced as satellite terminals to address congestion issues on bridges by allowing a proportion of drayage trucks to pick up and drop off containers at the ICD instead of going to the container terminals of the offshore ports. Containers are transported between the ICD and container terminals by inter-terminal transportation (ITT) trucks owned by port authorities. The ICD is expected to mitigate the bridge congestion by transferring the travel demands of drayage trucks in peak hours to the travel demands of ITT trucks in off-peak hours. We propose a methodology for analyzing the influence of ICDs on port efficiency. An integer linear programming model is developed to optimize the movements of containers, drayage trucks and ITT trucks in an offshore port area with the objective of minimizing the costs of drayage trucks and ITT trucks and the penalty for late delivery of containers. Two model transformation approaches are proposed to reduce the solution space of the model for improving the computational efficiency of the algorithm. The influence of ICDs on port efficiency is evaluated through a real-world case study using the proposed methodology. The results provide insights for port authorities to make strategic decisions. [ABSTRACT FROM AUTHOR]