A Clustering-Based Approach to the Multi-stage Facility Location Problem

Kezhong Wu, Yu Guan, Jinliang Li, Fan Lu, Yaoguang Hu

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

2 Citations (Scopus)

Abstract

This paper focuses on a special multi-stage facility location problem. The facility is a cluster of equipment that provides service. it is a special facility with high flexibility that can be moved at any time to respond to multi-stage maintenance requirements. This paper aims to find the optimal number of dynamic service facility and the location of each stage, so as to minimize the total cost. In order to solve this problem, two approach are proposed in this paper. The first approach adopt that strategy of front to back, using clustering based algorithm to get approximate optimal solution; The other is to use a strategy from the back to front, using a dynamic planning algorithm to get the global optimal solution. Numerical experiments are carried out to compare the two approach. The results show that the clustering-based algorithm has higher computational performance and can obtain reliable approximate optimal solution. Finally, we apply the clustering-based approach to real cases to provide a reliable solution for decision makers.

Original languageEnglish
Title of host publication2019 IEEE 6th International Conference on Industrial Engineering and Applications, ICIEA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages536-540
Number of pages5
ISBN (Electronic)9781728108513
DOIs
Publication statusPublished - 14 May 2019
Event6th IEEE International Conference on Industrial Engineering and Applications, ICIEA 2019 - Tokyo, Japan
Duration: 12 Apr 201915 Apr 2019

Publication series

Name2019 IEEE 6th International Conference on Industrial Engineering and Applications, ICIEA 2019

Conference

Conference6th IEEE International Conference on Industrial Engineering and Applications, ICIEA 2019
Country/TerritoryJapan
CityTokyo
Period12/04/1915/04/19

Keywords

  • clustering
  • dynamic environment
  • dynamic planning
  • facility location

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