Regression based integration of demand forecasting and inventory decision

  • Meng Hao Xi*
  • , He Xing Wang
  • , Qiu Hong Zhao
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the traditional inventory decision-making, demand forecasting and inventory control decisions are made independently, so it is difficult to ensure that the inventory cost is minimized. To make the demand forecasting and inventory control be consistent, this paper proposes a cost regression model, in which the demand forecasting is combined with the inventory decisions, aiming to minimize the inventory cost rather than the forecast error. A computational example is presented, to show the difference of the integrated decision-making model and the decentralized decision-making model.

Original languageEnglish
Title of host publicationMaterials Science and Information Technology, MSIT2011
Pages2954-2956
Number of pages3
DOIs
StatePublished - 2012
Event2011 International Conference on Material Science and Information Technology, MSIT2011 - Singapore, Singapore
Duration: 16 Sep 201118 Sep 2011

Publication series

NameAdvanced Materials Research
Volume433-440
ISSN (Print)1022-6680

Conference

Conference2011 International Conference on Material Science and Information Technology, MSIT2011
Country/TerritorySingapore
CitySingapore
Period16/09/1118/09/11

Keywords

  • Cost regression model
  • Demand forecasting
  • Inventory control

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