Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China
Author(s) -
Feng Pian,
Qiuju Shi,
Xue Yao,
Huiling Zhu,
Weixin Luan
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/5584600
Subject(s) - container (type theory) , joint (building) , china , port (circuit theory) , computer science , environmental science , agricultural engineering , operations research , mathematics , civil engineering , engineering , geography , mechanical engineering , archaeology
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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom