Abstract
This paper develops a location optimization method about the metro-based underground logistics system (MULS) to transport freight by metro during off-peak periods. First, we make qualitative and quantitative feasibility analysis of the MULS through questionnaires and field surveys in metro stations. The analysis result shows that more than 85.22% of interviewees support logistics delivery by the metro. An improved $p$ -median model is developed, which considers four influencing factors. The shortest path algorithm is used to minimize the transport costs while the costs of the remaining factors are calculated using the collected data. Then, the Voronoi diagram is adopted to optimize the location of candidate metro stations and redraw the logistics service scope by adding weighted terms. Finally, the Nanjing metro is chosen as a case study to validate the effectiveness of the developed method. The optimization result shows the total cost of the logistics delivery is reduced by 33. 27% suggesting that the method can be used to reduce logistics costs and improve delivery efficiency in urban areas.
Highlights
The underground logistics system (ULS) is known as the underground freight transport system (UFTS) [1]
One is how to choose a path around stations to minimize the transport cost. Another problem is how to take the points from candidate metro stations as delivery nodes and optimize each node’s service scope, to reduce the total cost of the system when carrying out the logistics delivery process
The number of metro stations that need to be used as logistics delivery nodes in the range of study is 8 calculate by (16)
Summary
The underground logistics system (ULS) is known as the underground freight transport system (UFTS) [1]. Kikuta et al [2] proposed a novel city logistics system by integrating the public metro service with conventional freight vehicles to transport goods effectively from the suburbs to the city center. Dampier and Marinov [3] selected the Tyne and Wear Metro system located in the Newcastle upon Tyne as the case study and discussed the feasibility of a metropolitan railway network to transport freight from the surrounding businesses to a city center. A summary of existing studies shows that scholars developed different models with different location optimization goals and network complexity.
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