| Literature DB >> 33716560 |
Abuduaini Abudureheman1, Aishanjiang Nilupaer1.
Abstract
In order to better accelerate the transition from traditional trade to cross-border e-commerce, a cross-border e-commerce transportation route optimization model was designed in the context of the prevention and control of new crown pneumonia. Against the background of the new coronavirus pneumonia, through the analysis and research of the current situation of domestic and foreign e-commerce logistics, optimize the cross-border e-commerce logistics distribution model, establish an environmental model, and use efficient search algorithms to search for walking paths that meet environmental requirements. Based on the Dijkstra algorithm model of demand, and based on the linear relationship between demand and delivery distance, an optimal route selection model is established to select the optimal route with the shortest total travel distance. The simulation results show that the cross-border e-commerce transportation time of this model is within 13 h, which is shorter than that of the traditional model. The search efficiency of the optimal route for cross-border e-commerce transportation is higher, and the time for cross-border e-commerce transportation is shorter.Entities:
Keywords: COVID-19 pneumonia; Cross-border e-commerce; Epidemic prevention and control; Transport path
Year: 2021 PMID: 33716560 PMCID: PMC7936583 DOI: 10.1007/s00500-021-05685-6
Source DB: PubMed Journal: Soft comput ISSN: 1432-7643 Impact factor: 3.643
Cross-border e-commerce distribution mode under the background of prevention and control of COVID-19 pneumonia
| Distribution mode | Form | Characteristic | |
|---|---|---|---|
| Provide home delivery service | Online transaction payment of goods directly delivered to the user's home | It brings convenience to online shopping customers, improves service quality, and brings users a good online shopping experience. However, there are also corresponding disadvantages. When delivering goods to the door, customers need to provide detailed receiving address, which may cause the leakage of personal information of online shopping customers, which poses a great challenge to the security and confidentiality mechanism of e-commerce system | |
| Self service delivery | |||
| Manual self-services pick up point | One is that logistics suppliers set up special pick-up points through self-construction, and the other is to cooperate with local stores to set up pick-up points, such as shops, pharmacies, community properties, etc | The cost of self-built mode is high, but the service is more professional: the cost of cooperation with stores is lower, and the service is more convenient | The cost of self-service delivery is lower, the information security of customers is high, and the time for customers to pick up goods is more flexible |
| Self service delivery cabinet | It is divided into public storage box and private receiving box. For example, Jingdong's pick-up container, Wal Mart store's locker, CoDeSys's skybox | It is more flexible in terms of security and time. Public storage boxes need a lot of capital investment in infrastructure. Private containers are for individual high-end groups, so they are not universal | |
Fig. 1Distribution process of cross-border e-commerce logistics center
Logistics distribution route selection conditions
| Category | Optimal path | Alternative path |
|---|---|---|
| Characteristic | The population is concentrated, and the scale of e-commerce transactions is large. The delivery address of express delivery is usually the work unit and the community where they live | Population living in villages and towns as the center, compared with the city is scattered |
| Problem | Almost no one is at home during working hours, and most communities do not allow express delivery personnel to enter directly, and work units do not allow employees to receive private express during working hours | The distribution points are far away from each other, the distribution efficiency is low and the distribution cost is high |
Fig. 2Framework of optimal selection model for e-commerce transportation path
Experimental parameters
| Project | Parameter |
|---|---|
| Operating platform | Windows NT |
| Number of CPU cores | 6 cores |
| Maximum capacity of detection system | 16 GB |
| Internal structure | X86 |
| Video card capacity | 8 GB |
| Hard disk type | Solid state drive |
| Interface connection mode | CAN Bus serial |
Fig. 3Optimal path search efficiency comparison test
Fig. 4Comparison of cross border e-commerce transportation efficiency