Online retailer product inventory decision-making method and system based on demand prediction

A technology of demand forecasting and decision-making methods, applied in the field of big data forecasting, can solve problems such as ignoring inaccuracies, and achieve the effect of optimizing inventory management

Pending Publication Date: 2022-04-29
HUAZHONG UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, due to the rapid development of Internet technology, in addition to traditional offline channels, users' shopping channels have become complex and diverse, which poses new challenges for online retailers to accurately predict demand and optimize inventory management
There are many existing technologies on demand forecasting and inventory management respectively. However, few technologies involve the fusion of demand forecasting and inventory management decisions. In addition, most of the technologies directly bring the forecast results into the optimization model, while ignoring the forecast possible inaccuracies

Method used

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  • Online retailer product inventory decision-making method and system based on demand prediction
  • Online retailer product inventory decision-making method and system based on demand prediction
  • Online retailer product inventory decision-making method and system based on demand prediction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0088] The following takes the nut inventory management of an online retailer as an example for illustration, which includes the following steps (see figure 1 ):

[0089] 101. Collect customer behavior data and online retailer product sales data:

[0090] Collect the sales data of the nut in the past year from the background of the system and all the click behavior and evaluation data of the nut in the store from the customers who have acted on the nut in the past year. The click behavior data includes customer clicks, favorites, purchases , shopping cart behavior, customer age, gender, customer stay time on different pages (search page, product home page, product detail page, evaluation page, recommendation page), and comment data includes customer comments about the nut in the store in the past year All comments, comments with pictures / videos, additional comments, positive comments, medium / bad comments, etc.

[0091] 102. Perform feature engineering on collected data:

[...

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Abstract

The invention discloses an online retailer product inventory decision-making method and system based on demand prediction, and belongs to the field of big data prediction and operation optimization. Comprising the steps of predicting demands of each ordering period in a product ordering period of an online retailer; converting the predicted demand of the product in each order period into a fuzzy demand by using a triangular fuzzy number; substituting the fuzzy demand of the product in each order period into the inventory optimization decision model and solving to obtain the optimal order quantity of the product in each order period; according to the method, the situation that prediction is not always accurate is considered, and demand prediction and an inventory optimization model are fused together through fuzzy demands. The product demand of an online retailer is predicted by using big data and a big data analysis technology, a prediction result is converted into a fuzzy demand based on a triangular fuzzy demand, and the fuzzy demand is substituted into a dynamic batch model to solve the problem of the multi-cycle optimal ordering number of products. And technical support can be provided for enterprises to perform inventory optimization management by applying big data.

Description

technical field [0001] The invention belongs to the field of big data forecasting, and more particularly relates to a method and system for making inventory decisions of online retailers based on demand forecasting. Background technique [0002] We are in the era of data explosion, how to effectively use data and improve the operation and management of enterprises is one of the key factors for enterprises to gain an advantage in competition. Different from traditional retailers, online retailers have a large amount of user data, such as user click stream data, online review data, etc. In addition, due to the rapid development of Internet technology, in addition to traditional offline channels, users' shopping channels have become complex and diverse, which poses new challenges for online retailers to accurately predict demand and optimize inventory management. There are many existing technologies on demand forecasting and inventory management respectively. However, few tech...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06Q10/08
CPCG06Q30/0202G06Q30/0201G06Q10/087
Inventor 徐贤浩陈程
Owner HUAZHONG UNIV OF SCI & TECH
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