The complex landforms of a Shan-shui City(Shan-shui refers to mountains and rivers)significantly impact the selection of locations for logistics enterprises.This paper takes Chongqing,one of the most typical Shan-shui...The complex landforms of a Shan-shui City(Shan-shui refers to mountains and rivers)significantly impact the selection of locations for logistics enterprises.This paper takes Chongqing,one of the most typical Shan-shui Cities in China,as the research object,and adopts spatial analysis methods and a mediating effect model,to explore the role of mountains and rivers in the formation of logistics enterprises’spatial pattern on the street scale.The study results reveal that 90% of the logistics enterprises in the central urban areas of Chongqing are located in the low-altitude area below 353m above sea level,and distributed in a north-south direction along the mountains,as a result of blockage by mountain ranges,such as those of Zhongliang Mountain and Tongluo Mountain.More than 70% of the logistics enterprises are located less than 5 km from either the Yangtze River or Jialing River,spreading along the rivers.In addition,more than half of the logistics enterprises in commercial and financial,and residential land are located within the urban core area,while 80.83% of the logistics enterprises located in warehousing land and industrial land are concentrated in the urban expansion area.In areas with high land prices,the negative effect of altitude on logistics enterprise agglomeration is weakened,while the promotion effect of river proximity on logistics enterprise agglomeration is enhanced.In the urban core area with the advantage of low altitude and proximity to the Jialing and Yangtze Rivers,the role of mountains and rivers on logistics enterprises is not apparent;in contrast,in the urban expansion area with more complex landforms,land price can be an effective means for the government to macro-manage the spatial pattern of logistics enterprises in a Shan-shui City.展开更多
This paper intends to complete the primary logistics planning of oil products under the imbalance of supply and demand. An integrated mathematical programming model is developed to simultaneously find the balance betw...This paper intends to complete the primary logistics planning of oil products under the imbalance of supply and demand. An integrated mathematical programming model is developed to simultaneously find the balance between supply and demand, and optimize the logistics scheme. The model takes minimum logistics cost and resource adjustment cost as the objective function, and takes supply and demand capacity, transportation capacity, mass balance, and resource adjustment rules as constraints.Three adjustment rules are considered in the model, including resource adjustment within oil suppliers,within oil consumers, and between oil consumers. The model is tested on a large-scale primary logistics of a state-owned petroleum enterprise, involving 37 affiliated refineries, 31 procurement departments,286 market depots and dedicated consumers. After the unified optimization, the supply and demand imbalance is eased by 97% and the total cost is saved by 7%, which proves the effectiveness and applicability of the proposed model.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.72173101)sponsored by Natural Science Foundation of Sichuan,China(2022NSFSC0417)。
文摘The complex landforms of a Shan-shui City(Shan-shui refers to mountains and rivers)significantly impact the selection of locations for logistics enterprises.This paper takes Chongqing,one of the most typical Shan-shui Cities in China,as the research object,and adopts spatial analysis methods and a mediating effect model,to explore the role of mountains and rivers in the formation of logistics enterprises’spatial pattern on the street scale.The study results reveal that 90% of the logistics enterprises in the central urban areas of Chongqing are located in the low-altitude area below 353m above sea level,and distributed in a north-south direction along the mountains,as a result of blockage by mountain ranges,such as those of Zhongliang Mountain and Tongluo Mountain.More than 70% of the logistics enterprises are located less than 5 km from either the Yangtze River or Jialing River,spreading along the rivers.In addition,more than half of the logistics enterprises in commercial and financial,and residential land are located within the urban core area,while 80.83% of the logistics enterprises located in warehousing land and industrial land are concentrated in the urban expansion area.In areas with high land prices,the negative effect of altitude on logistics enterprise agglomeration is weakened,while the promotion effect of river proximity on logistics enterprise agglomeration is enhanced.In the urban core area with the advantage of low altitude and proximity to the Jialing and Yangtze Rivers,the role of mountains and rivers on logistics enterprises is not apparent;in contrast,in the urban expansion area with more complex landforms,land price can be an effective means for the government to macro-manage the spatial pattern of logistics enterprises in a Shan-shui City.
基金partially supported by the National Natural Science Foundation of China (51874325)the Science Foundation of China University of PetroleumBeijing (2462021BJRC009)。
文摘This paper intends to complete the primary logistics planning of oil products under the imbalance of supply and demand. An integrated mathematical programming model is developed to simultaneously find the balance between supply and demand, and optimize the logistics scheme. The model takes minimum logistics cost and resource adjustment cost as the objective function, and takes supply and demand capacity, transportation capacity, mass balance, and resource adjustment rules as constraints.Three adjustment rules are considered in the model, including resource adjustment within oil suppliers,within oil consumers, and between oil consumers. The model is tested on a large-scale primary logistics of a state-owned petroleum enterprise, involving 37 affiliated refineries, 31 procurement departments,286 market depots and dedicated consumers. After the unified optimization, the supply and demand imbalance is eased by 97% and the total cost is saved by 7%, which proves the effectiveness and applicability of the proposed model.