Truck scheduling optimization for port collection and distribution based on multi-dimensional space-time network

This paper studies the integrated optimization of two-way truck scheduling for import and export container collection and distribution of port and surrounding hinterland with time window constraints. A multi-dimensional time-space-state network was constructed based on the physical network to dynamically reflect the spatio-temporal trajectory and loading conditions of trucks. Aiming at maximizing the container volume of collection and distribution, minimizing the total transport cost and the amount of trucks dispatched, a multi-objective integer programming model was formulated to optimize the truck scheduling for port container collection and distribution based on service network. Taking the short distance import and export container collection and distribution in Shanghai Port of the Yangtze Delta as an example, the Gurobi9.5.2 was used to solve the optimization model. The results indicated that the multi-dimensional time-space-state network can rationally plan the truck routes and collecting and distributing process, thus achieving the integrated optimization of two-way truck scheduling for port container collection and distribution with time window constraints while dynamically reflecting the spatio-temporal trajectory and loading conditions of trucks. These inferences are expected to serve as a theoretical support for sustainable source of port collection and distribution.