Simulation of the Optimal Location for a Distribution Center of E-Commerce Operations in São Paulo State

Brasileiro, Luzenira Alves; Chiuffa, Vinicius Patrocollo Domingos

doi:10.1109/tla.2018.8444401

Cited by 6 publications

(5 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The business recommendation system can not only quickly help customers find the required commodity information in a variety of complex information but also compare the commodity information and help customers judge [7]. For merchants, the recommendation system can also record customer information and can also carry out corresponding business promotion activities to customers through the platform and lay the foundation for recooperation with customers [8]. In order to better attract customers, help customers find the products they need and improve the quality of sales, and product recommendation systems are gradually being applied to e-commerce websites [9].…”

Section: Introductionmentioning

confidence: 99%

Precision Marketing Optimization Model of e-Commerce Platform Based on Collaborative Filtering Algorithm

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

e-commerce mode shows great modern commercial value. In particular, online shopping has become a fashion and trend for people because of its convenience and rapidness. How to find the information users that need accurately and quickly in the increasing network information and recommend products is a big problem. Although precision marketing was mainly used in e-commerce activities in the past, due to factors such as the technical basis and data analysis ability at that time, there was not enough technical ability and theoretical basis to deeply mine and make use of the existing data. The collaborative filtering algorithm is one of the most widely used and successful recommendation techniques, but it has obvious defects. In this paper, the nearest neighbor collaborative filtering recommendation algorithm based on statistical eigenvalue classification is proposed in the collaborative filtering algorithm. By calculating the similarity between items, the user’s rating of unrated items is preliminarily predicted, the nearest neighbor of items is formed, and the classified cluster of items is formed. The matrix is filled by the similarity between related items. The cold treatment problem is solved under the optimization of the ant colony algorithm. In the experiment of the model, the optimization rate for the cold start problem is 87.3%.

show abstract

Section: Introductionmentioning

confidence: 99%

Precision Marketing Optimization Model of e-Commerce Platform Based on Collaborative Filtering Algorithm

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…Finally we use equation (11) to determine all the cut points, where  is a threshold value and the size of  has a direct effect on the complexity of the tree, when 0 Gain  , the larger the value the more worthy the cut.…”

Section: Convolution and Xg Fusion Prediction Model Structurementioning

confidence: 99%

“…The literature [11] examines the ideal distribution center location for conducting e-commerce operations in So Paulo. The authors used simulation methods to evaluate the effects of different locations to determine the optimal location.…”

mentioning

confidence: 99%

Feasibility study of deep learning based on data-based e-commerce operations

Yue

2023

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

In this paper, we first study data-based e-commerce operation from the big data perspective and elaborate on data-based e-commerce operation from four aspects: professional terminology, operation core, theoretical operation basis, and operation method. Secondly, in the process of e-commerce data-based operation sales prediction, data pre-processing and feature selection are required, and the quality of data and features directly determines the accuracy of the model and based on deep learning, the structure of convolutional and XG fusion prediction model is proposed. Then, three-dimensional data frames are constructed based on four-dimensional data facets, which leads to more accurate model predictiveness, and the prediction model and e-commerce financial and operational risks are studied and analyzed. The results show that the convolutional and XG fusion forecasting model has a greater efficiency enhancement function than the traditional data computation model in the practical application of the forecasting model, proving the model’s stability in the long-term forecasting process. By predicting risk in e-commerce operations in time and improving it in real-time, this study can help the enterprise develop more competitively.

show abstract

“…Based on the numerical measurements of the simulation analysis, they verified the validity of the site selection analysis framework. The selected city of JAU meets the advantages of low logistic costs and high transportation efficiency, which can be used as a suitable The selected JAU city meets the advantages of low logistics cost and high transportation efficiency and can be a suitable logistics distribution center [17]. Xiao, K. et al proposed a logistics warehouse center framework with the fuzzy method and neural network framework as the underlying architecture as well as a marketing strategy to optimize the operation of e-commerce logistics, which effectively improves logistics and transportation efficiency.…”

Section: Introductionmentioning

confidence: 99%

Intelligent e-commerce logistics path planning and scheduling optimization combined with graph theory

Li,

2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

Solving logistics and distribution problems through intelligent algorithms can strongly improve the market core competitiveness of e-commerce logistics enterprises. This paper maps the distribution station location in e-commerce logistics to graph theory nodes and establishes the logistics path planning model. Then use the binary group to improve the Dicoscher algorithm to solve the planning of the e-commerce logistics path, and through the genetic algorithm to solve the objective function of the cost and other factors in the logistics scheduling to achieve the logistics cost concessions, and ultimately build the e-commerce logistics planning and scheduling optimization strategy. The analysis of the application effect of constructing the path planning and optimization strategy finds that the distribution distance of the logistics path solved by this paper’s algorithm under the condition of 20 distribution points is 80.47km shorter than that of the ant colony algorithm. The total cost spent on the path is 799.75 yuan on average, and the time consumed is only 62.14s. Meanwhile, it has been found that after implementing the path planning strategy, the total working time of the dispatcher decreases by 28.6 hours, and the pressure of the job significantly decreases. The e-commerce logistics path planning and scheduling optimization method designed in this paper provides an effective solution for cost-saving in logistics enterprises.

show abstract

Simulation of the Optimal Location for a Distribution Center of E-Commerce Operations in São Paulo State

Cited by 6 publications

References 7 publications

Precision Marketing Optimization Model of e-Commerce Platform Based on Collaborative Filtering Algorithm

Precision Marketing Optimization Model of e-Commerce Platform Based on Collaborative Filtering Algorithm

Feasibility study of deep learning based on data-based e-commerce operations

Intelligent e-commerce logistics path planning and scheduling optimization combined with graph theory

Contact Info

Product

Resources

About