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

In order to solve the problems of poor timeliness and high service cost caused by international logistics of cross-border e-commerce and to realize the localization of cross-border trade and improve consumers' shopping experience, much cross-border e-commerce has introduced overseas warehouse business. Because the optimization model for the logistics distribution network of cross-border e-commerce cannot solve the problem of high operation cost, the optimization model for the logistics distribution network of cross-border e-commerce based on a personalized recommendation algorithm is designed. Through the analysis of the logistics distribution network of cross-border e-commerce structure and the construction of logistics distribution network of cross-border e-commerce model and multiobjective optimization of logistics distribution network of cross-border e-commerce, the construction process of the logistics distribution network optimization model is completed. The simulation results verify the effectiveness of the model. By comparison, this model can effectively solve the problems that the original model cannot solve and reduce the operation cost of the logistics distribution network.

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Operation Optimization of DC Distribution Network with BSS Based on GA-WDO Hybrid Algorithm

Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) ◽

10.2174/2352096513999200422142041 ◽

2020 ◽

Vol 13 (7) ◽

pp. 1087-1096

Author(s):

Yang Wang ◽

Fengyun Chen ◽

Wen Xiao ◽

Zhengming Li

Keyword(s):

Power Generation ◽

Objective Function ◽

Optimization Model ◽

Distribution System ◽

Distribution Network ◽

Minimum Variance ◽

Utilization Rate ◽

Solar Absorption ◽

Dc Distribution ◽

Operation Cost

Background: The high permeability of Distributed Generation (DG) and the development of DC load represented by electric vehicle Battery Swapping Station (BSS) pose new challenges to the reliable and economic operation of DC distribution system. Methods: In order to improve the wind and solar absorption rate and the reliable operation of DC distribution network and coordinate the interests and demands of BSS and DC distribution company, the upper level takes the abandonment rate and the minimum variance of BSS charging and discharging net load as two objective functions, and the lower level takes the minimum operation cost of DC distribution network and BSS as the objective function. Secondly, this paper proposes a method that combines Genetic Algorithm (GA) with Wind-Driven Optimization algorithm (WDO). CPLEX and hybrid GA-WDO are used to solve the upper and lower models, respectively. Results: Finally, an example shows that the proposed optimization model can reduce the operation cost of DC distribution network with BSS and improve the utilization rate of wind and light, which shows the rationality and effectiveness of the optimization model. Conclusion: In this paper, considering the randomness and uncertainty of wind power generation and photovoltaic power generation, this paper establishes the upper objective function with the minimum abandonment rate and load variance and the lower objective function with the minimum operation cost of DC distribution network and BSS operators.

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Cross-Border E-Commerce Personalized Recommendation Based on Fuzzy Association Specifications Combined with Complex Preference Model

Mathematical Problems in Engineering ◽

10.1155/2020/8871126 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Dan Xiang ◽

Zhijie Zhang

Keyword(s):

Association Rule ◽

Recommendation System ◽

Real Life ◽

User Preference ◽

Personalized Recommendation ◽

Recommendation Algorithm ◽

Fuzzy Association Rules ◽

Cross Border ◽

Fuzzy Association Rule ◽

The Impact

Since cross-border e-commerce involves the export and import of commodities, it is affected by many policies and regulations, resulting in some special requirements for the recommendation system, which makes the traditional collaborative filtering recommendation algorithm less effective for the cross-border e-commerce recommendation system. To address this issue, a simple yet effective cross-border e-commerce personalized recommendation is proposed in this paper, which integrates fuzzy association rule and complex preference into a recommendation model. Under the constraint of fuzzy association rules, a hybrid recommendation model based on user complex preference features is constructed to mine user preference features, and personalized commodities recommendation is realized according to user behavior preference. Compared with the traditional recommendation algorithm, the improved algorithm reduces the impact of data sparsity. The experiment also verifies that the improved fuzzy association rule algorithm has a better recommendation effect than the existing state-of-the-art recommendation models. The recommendation system proposed in this paper has better generalization and has the performance to be applied to real-life scenarios.

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Research on Enterprise Supply Chain Optimization Model and Algorithm Based on Fuzzy Clustering

Journal of Mathematics ◽

10.1155/2021/4827903 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Shizhen Bai ◽

Hongbin Sun

Keyword(s):

Supply Chain ◽

Fuzzy Clustering ◽

Network Structure ◽

Optimization Model ◽

Economies Of Scale ◽

Clustering Algorithm ◽

Distribution Network ◽

Supply Chain Optimization ◽

Logistics Distribution ◽

Logistics Enterprises

Reasonable logistics distribution network structure can not only effectively reduce the cost of logistics enterprises themselves but also reduce the social cost. Through effective supply chain management, enterprises can significantly reduce costs, improve competitiveness, and enhance their ability to resist risks. Because the single-level distribution network structure of production enterprises is not suitable for large-scale logistics distribution, this paper proposes a distribution network structure design that accords with economies of scale and establishes an enterprise supply chain optimization model based on the fuzzy clustering algorithm. Using this optimization method to optimize the inventory of enterprise logistics supply chain, the operation is fast, the result is correct and reasonable, and it can provide good decision support for the distribution network of logistics enterprises. Through information technology and modern management technology, we should effectively control and coordinate the logistics, information flow, and capital flow in the production and operation process and organically integrate the internal supply chain with the external supply chain for management, so as to achieve the goal of global optimization.

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