Abstract
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.
Highlights
In the process of economic and social development, the deployment and optimization of Cyber-Physical Systems play an increasingly important role
Compared with the RD mode, the total costs of the RD–RD-RL mode, RD-RL–RD mode, and RD-RL mode are lower by 17.85%, 18.92%, and 21.67%, respectively. e results reveal that the container multimodal transport mode of dry port transshipment can effectively reduce the total transportation cost. e RD-RL mode is the best transport mode with the optimal total transport cost. is indicates that whether the railway can reach the seaport directly has a significant impact on reducing the cost of container transportation
Under the RD-RL-RD mode, seven dry ports need to be built in Northeast China, including two fourth-level dry ports: Shenyang and Changchun, with a utilization rate of 100%; one third-level dry port: Harbin, with a utilization rate of 100%; one secondlevel dry port: Yanbian Korean Autonomous Prefecture, with a utilization rate of 54.17%; and three first-level dry ports: Chaoyang, Liaoyuan, and Hulunbuir, with an average utilization rate of 83.30%, all of which carry 79.88% of the container transshipment volume
Summary
In the process of economic and social development, the deployment and optimization of Cyber-Physical Systems play an increasingly important role. Reductions of cost, energy consumption, and carbon emissions of inland container transportation contribute to the Complexity sustainable development of the Chinese economy, especially to the logistics industry [11]. As an important logistics node in the inland container transportation network, the location layout, scale, quantity, and service area of the dry port have important contributions to the efficiency of the entire transportation chain. Is study measures the economic and environmental benefits of developing a dry port, considers the dry port’s carrying capacity, sets up its construction and operational costs at different scale levels, quantifies the time and carbon emission costs, builds the location model of the dry port, seeks the optimal scheme of inland container transportation, and takes Northeast China as an example. Based on the freight distribution of the foreign trade container volume, the optimal number of dry ports, location layout, service scope, and transportation scheme of the region are obtained to prove the effectiveness of the model
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