Hybrid Covering Location Problem: Set Covering and Modular Maximal Covering Location Problem

R. Alizadeh, T. Nishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

To benefit from the location advantages provided from two main covering location problems, namely set covering location problem and maximal covering location problem, a new mathematical model is presented in this study. In this model, the main facilities are located gradually through the planning periods, providing full coverage for the incremental demand of nodes. In addition, a limited number of modules are assigned to the located facilities to maximize the covered demand nodes in operational periods. Combining the set covering and maximal covering location problems in one model, to take advantage of the merits of both models is studied. Some test problems are solved to investigate the proposed model. The numerical results confirm the applicability of the model and provide insights for the proposed model.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019
PublisherIEEE Computer Society
Pages865-869
Number of pages5
ISBN (Electronic)9781728138046
DOIs
Publication statusPublished - Dec 2019
Externally publishedYes
Event2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019 - Macao, Macao
Duration: Dec 15 2019Dec 18 2019

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Conference2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019
Country/TerritoryMacao
CityMacao
Period12/15/1912/18/19

Keywords

  • Dynamic
  • Set covering
  • hybrid mathematical model
  • maximal covering
  • modular

ASJC Scopus subject areas

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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