An Optimization Model for Logistics Distribution Network of Cross-Border E-Commerce Based on Personalized Recommendation Algorithm

Zhang, Zhongqiang

doi:10.1155/2021/5510481

Cited by 18 publications

(16 citation statements)

References 15 publications

(15 reference statements)

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“…With the rapid development of the world economy, e-commerce, communication, and information technology, the traditional e-commerce model is difficult to adapt to the development and needs of modernization, and new needs continue to emerge. In particular, the emergence of emerging technologies such as Internet of Things technology and cloud computing technology has made the above-mentioned ecommerce distribution needs to be met technically; the emergence of new models can solve the sorting bottleneck problem in the e-commerce environment [6].…”

Section: Literature Reviewmentioning

confidence: 99%

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E-Commerce Sorting Equipment and System Based on Cloud Computing

Chen

2022

Wireless Communications and Mobile Computing

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In order to solve the problems of order reduction and customer churn caused by sorting delays, the author proposes a method for e-commerce sorting equipment based on cloud computing. This method mainly adopts double-layer sorting equipment; compared with single-layer automatic sorting equipment, double-layer sorting equipment has the characteristics of higher efficiency and smaller floor space. The sorting method adopts the “group sorting” method, which can effectively improve the sorting efficiency of the sorting equipment. The algorithm method adopts the mathematical model based on cloud computing for calculation. Experimental Results. The author adopts the cloud computing-based “composition sorting” double-layer sorting equipment; compared with the traditional single-layer sorting equipment, the throughput of the single-layer sorting strategy is 0.72 pieces/s when the conveying speed of the conveyor belt is the same, the throughput of the two-layer same-direction strategy is 1.46 pieces/s, the throughput of the balanced load strategy is 1.97 pieces/s, and the throughput of the group sorting load strategy is 2.57 pieces/s. This method can effectively solve the problems of order reduction and customer churn caused by sorting delays.

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Section: Literature Reviewmentioning

confidence: 99%

“…1 package supply table, the package must exit the warehouse through the a-side sorting compartment. Constraint (6) means that if the package enters the lower conveyor belt from the no. 2 package supply table, the package must exit the warehouse through the Bside sorting compartment.…”

Section: Minfmentioning

confidence: 99%

E-Commerce Sorting Equipment and System Based on Cloud Computing

Chen

2022

Wireless Communications and Mobile Computing

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“…It has been proved that the three-layer BP neural network can realize the accurate mapping of multidimensional space RM to RN. Although increasing the number of layers can further improve the accuracy and reduce the error, it also increases the complexity of the network, thus increasing the training time of the network [15]. Therefore, unless special circumstances, priority can be given to reducing network error and improving accuracy by appropriately increasing the number of hidden layer neurons on the basis of three-layer BP neural network.…”

Section: Bp Neural Network Designmentioning

confidence: 99%

Application of BP Neural Network in Matching Algorithm of Network E-Commerce Platform

Zhang

2022

Journal of Sensors

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In order to solve the matching algorithm problem of network e-commerce platform, a method of applying BP neural network in the network e-commerce platform matching algorithm is proposed. First of all, combined with the actual situation of the platform, select 9 factors that are most in line with the company’s actual business model to influence the selection for analysis; secondly, import 60 sets of data into MATLAB software, measure the input and output data uniformly, and divide the sample data matrix into training set and test. Finally, after multiple factor combinations and verifications, it is concluded that in the training model of the five main factors, the prediction results of the model are compared with the real values. The feasibility of establishing the selection model based on BP neural network is proved. Online e-commerce platforms can refer to this model to build a product selection model that meets the needs of the platform, helping enterprises to achieve more efficient product selection work. Since the parameter initialization of the neural network is random, although the output results are different after the program runs for many times, the R2 is still stable between 0.7 and 1.0, which proves that the predicted value made by the system is highly approximate to the real value and can achieve the predicted effect.

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“…In the process of cross-border e-commerce cold chain supply inventory planning, the cross-border e-commerce cold chain enterprises are taken as the core of the whole supply chain, and the internal personnel of the core enterprises are controlled and guided. Among them, the cross-border e-commerce enterprises focus on the control of information flow, logistics, and capital flow [12,13]. e cross-border e-commerce supply chain structure chart shown in Figure 3 is established by combining the most advanced technologies and equipment at the present stage.…”

Section: Construction Of the Node Importance Evaluation Systemmentioning

confidence: 99%

A Cross-Border e-Commerce Cold Chain Supply Inventory Planning Method Based on Risk Measurement Model

Liu¹

2022

Mobile Information Systems

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Inventory planning results are less reliable when the statistical problem of supply chain risk factors is not considered. In conjunction with the risk measurement model, a cross-border e-commerce cold chain supply inventory planning method is proposed to effectively address the aforementioned issues. This paper aims to define the fundamental elements of the supply chain network, determine the supply chain's imbalance range, and develop a risk measurement model and also to calculate the ordering cost and storage cost, the storage cost, the cross-border e-commerce imbalance index based on the risk measurement model, the node imbalance, the dynamic programming algorithm for the imbalance node, and the identification method for the cross-border e-commerce supply chain imbalance node. Taking inventory strategy into account, the optimization model of distribution node location and the node importance evaluation system are developed. The planning of cold chain supply inventory for cross-border e-commerce is studied based on an optimized management inventory. The experimental results indicate that the throughput of the research method is between 1000 and 2500 Mbps, that the overall fluctuation range and delay are small, and that the inventory turnover rate has been significantly increased, thereby satisfying the requirements of engineering materials inventory management.

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An Optimization Model for Logistics Distribution Network of Cross-Border E-Commerce Based on Personalized Recommendation Algorithm

Cited by 18 publications

References 15 publications

E-Commerce Sorting Equipment and System Based on Cloud Computing

E-Commerce Sorting Equipment and System Based on Cloud Computing

Application of BP Neural Network in Matching Algorithm of Network E-Commerce Platform

A Cross-Border e-Commerce Cold Chain Supply Inventory Planning Method Based on Risk Measurement Model

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