Demand Forecasting Models With Time Series and Random Forest

Tayalı H. A.

in: Driving Innovation and Productivity Through Sustainable Automation, Ardavan Amini,Stephen Bushell,Arshad Mahmood, Editor, IGI Global, Pennsylvania, pp.76-99, 2021

  • Publication Type: Book Chapter / Chapter Vocational Book
  • Publication Date: 2021
  • Publisher: IGI Global
  • City: Pennsylvania
  • Page Numbers: pp.76-99
  • Editors: Ardavan Amini,Stephen Bushell,Arshad Mahmood, Editor
  • Istanbul University Affiliated: Yes


This chapter presents the recent methodological developments in demand management and demand forecasting subjects of the operations management. The background section provides detailed information on the domain of production management, operational analytics, and demand forecasting while providing introductory information on time series forecasting and related machine learning methodologies. The novel contribution of the chapter is the exploration developed in the solutions and recommendations section while examining the effect of stationarity in the time series forecasting methodologies of machine learning with improved benchmark results.