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LOCATION AND INVENTORY OPTIMIZATION MODEL OF SPARE PARTS WAREHOUSE BASED ON UNCERTAINTY THEORY

  • Yi Yang
  • , Wei Liu
  • , Meilin Wen*
  • , Yong Qin*
  • , Tingting Zeng
  • , Siyu Huang
  • *Corresponding author for this work
  • Beihang University
  • Peng Cheng Laboratory
  • Beijing Jiaotong University

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

Abstract

In equipment integrated logistics support, support activities and support resources have a vital impact on the availability of equipment system. Spare parts warehouse location and inventory strategy will directly affect spare parts supply, and finally affect the system operation. Therefore, this paper establishes an optimization model of spare parts warehouse location considering inventory strategy. In order to deal with the epistemic uncertainty of spare parts demand, the uncertainty theory is introduced. The model aims at reducing the comprehensive support cost, adds the supportability parameters to the model constraints, and optimizes the inventory control and spare parts warehouse location as a whole. The genetic algorithm is used to solve the model, and the optimal location scheme and inventory strategy meeting the supportability constraints are obtained. Based on the proposed model and calculation results, the accuracy of equipment support can be improved and the support cost can be reduced as much as possible on the premise of ensuring equipment availability.

Original languageEnglish
Title of host publicationIET Conference Proceedings
PublisherInstitution of Engineering and Technology
Pages1269-1273
Number of pages5
Volume2022
Edition13
ISBN (Electronic)9781839537837
DOIs
StatePublished - 2022
Event1st International Conference on Mechanical System Dynamics, ICMSD 2022 - Nanjing, China
Duration: 24 Aug 202227 Aug 2022

Conference

Conference1st International Conference on Mechanical System Dynamics, ICMSD 2022
Country/TerritoryChina
CityNanjing
Period24/08/2227/08/22

Keywords

  • LOCATION AND INVENTORY CONTROL
  • SPARE PARTS MANAGEMENT
  • UNCERTAIN P ROGRAMMING MODEL

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