4.5 Article

Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China

Journal

COMPLEXITY
Volume 2021, Issue -, Pages -

Publisher

WILEY-HINDAWI
DOI: 10.1155/2021/5584600

Keywords

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Funding

  1. Key Project of Natural Science Foundation of China [42030409]
  2. Youth Program of National Natural Science Foundation of China [41701134]
  3. National Natural Science Foundation of China [41671117]
  4. Postdoctoral Science Foundation of China [2019M651098]

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This study calculates the costs associated with dry port construction and operations, transportation, time, and the environment, and constructs a joint optimization model to minimize the total cost. Through empirical analysis, it was found that building seven dry ports in the road-rail mode in Northeast China could significantly reduce the economic and environmental costs of container transportation.
Dry port construction can reduce the cost of container transportation, and its location is the focus of existing research. Considering dry port capacity limitations and scale advantages, this study calculates the costs associated with dry port construction and operations, transportation, time, and the environment and constructs a joint optimization model of the dry port location and transportation scheme to minimize the total cost. Taking 35 prefecture-level cities in Northeast China as the source of container goods and Dalian port as the destination, this study conducts an empirical analysis using the Gurobi 9.0.2 optimizer of the AMPL software to solve the problem and takes the minimum total cost as the goal to select the best dry port and container transshipment scheme. The research draws the following conclusions. Seven dry ports also need to be built in the road-rail (RD-RL) mode, which shares 82.76% of the container transshipment volume, to reduce the total transportation cost by approximately 21.67%. Although multimodal transport through dry ports increases the time cost slightly, it can significantly reduce the economic and environmental costs of container transportation.

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