Optimizing The Design Of An Intra-City Metro Logistics System Based On A Hub-And-Spoke Network Model

Developing a combined surface road and underground logistics system based on a city's metro network is a sustainable solution to alleviate urban traffic congestion and environmental pollution problems. In this study, we propose a three-stage optimization model with a two-level hub-and-spoke structure to establish an intra-city metro logistics network. First, we establish an entropy-weighted TOPSIS model to rank the transshipment capacity of metro stations based on four network centrality indicators, and use the results as the basis to classify metro stations into candidate hub and spoke nodes. Second, we establish a maximum-coverage location model that accounts for capacity constraints, and use a greedy randomized adaptive search procedure to identify spoke nodes. Third, with the objective of minimizing the transport distance within the whole network, we solve the hub-and-spoke network planning problem with capacity constraints by using a tabu search algorithm to identify the hub nodes. Finally, we take Shanghai as an empirical case study to demonstrate a suitable layout optimization scheme for Shanghai's metro logistics network. Through sensitivity analysis, we then analyze the impact of different capacity parameters on the layout of the network.