A Machine Learning Predictive Model for Shipment Delay and Demand Forecasting for Warehouses and Sales Data

K. L. Keung, C. K.M. Lee, Y. H. Yiu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In the era of Industry 4.0, various technologies have been great assisting tools for different industries to improve their work efficiency and enhance customers' satisfaction and loyalty. This paper discusses the issue of shipment delay and sales prediction by understanding how various attributes, based on data from the retail industry, will impact on their result. It was found that the locational factors and product category have been determining fluctuating sales or prominent delays. The results of machine learning algorithms are also discussed on how a better correlation in forecast and attribute relationships can be attained.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1010-1014
Number of pages5
ISBN (Electronic)9781665437714
DOIs
Publication statusPublished - Dec 2021
Event2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021 - Virtual, Online, Singapore
Duration: 13 Dec 202116 Dec 2021

Publication series

Name2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021

Conference

Conference2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
Country/TerritorySingapore
CityVirtual, Online
Period13/12/2116/12/21

Keywords

  • Demand forecasting
  • Machine Learning
  • Predictive model
  • Shipment delay
  • Warehouse

ASJC Scopus subject areas

  • Strategy and Management
  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management
  • Industrial and Manufacturing Engineering
  • Control and Optimization

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