Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China
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 t...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5584600 |
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| _version_ | 1832554078163435520 |
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| author | Feng Pian Qiuju Shi Xue Yao Huiling Zhu Weixin Luan |
| author_facet | Feng Pian Qiuju Shi Xue Yao Huiling Zhu Weixin Luan |
| author_sort | Feng Pian |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-407ec4adc4b841ddaccbfe926abc860f |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-407ec4adc4b841ddaccbfe926abc860f2025-02-03T05:52:26ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55846005584600Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast ChinaFeng Pian0Qiuju Shi1Xue Yao2Huiling Zhu3Weixin Luan4School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, ChinaSchool of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, ChinaSchool of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, ChinaCollege of Transportation Engineering, Dalian Maritime University, Dalian 116026, ChinaSchool of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, ChinaDry 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.http://dx.doi.org/10.1155/2021/5584600 |
| spellingShingle | Feng Pian Qiuju Shi Xue Yao Huiling Zhu Weixin Luan Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China Complexity |
| title | Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China |
| title_full | Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China |
| title_fullStr | Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China |
| title_full_unstemmed | Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China |
| title_short | Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China |
| title_sort | joint optimization of a dry port with multilevel location and container transportation the case of northeast china |
| url | http://dx.doi.org/10.1155/2021/5584600 |
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