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ID 61346
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Author
Alizadeh, Roghayyeh Division of Mathematical Science for Social Systems, Department of Systems Innovation, Graduate School of Engineering Science, Osaka University
Nishi, Tatsushi Graduate School of Natural Sciences, Department of Industrial Innovation Engineering, Okayama University ORCID Kaken ID researchmap
Bagherinejad, Jafar Department of Industrial Engineering, Faculty of Engineering, Alzahra University
Bashiri, Mahdi School of Strategy and Leadership, Faculty of Business and Law, Coventry University
Abstract
The paper aims to study a multi-period maximal covering location problem with the configuration of different types of facilities, as an extension of the classical maximal covering location problem (MCLP). The proposed model can have applications such as locating disaster relief facilities, hospitals, and chain supermarkets. The facilities are supposed to be comprised of various units, called the modules. The modules have different sizes and can transfer between facilities during the planning horizon according to demand variation. Both the facilities and modules are capacitated as a real-life fact. To solve the problem, two upper bounds-(LR1) and (LR2)-and Lagrangian decomposition (LD) are developed. Two lower bounds are computed from feasible solutions obtained from (LR1), (LR2), and (LD) and a novel heuristic algorithm. The results demonstrate that the LD method combined with the lower bound obtained from the developed heuristic method (LD-HLB) shows better performance and is preferred to solve both small- and large-scale problems in terms of bound tightness and efficiency especially for solving large-scale problems. The upper bounds and lower bounds generated by the solution procedures can be used as the profit approximation by the managerial executives in their decision-making process.
Keywords
maximal covering location problem
capacitated facility
modularity
multi-period
Lagrangian decomposition heuristic
Published Date
2021-01-04
Publication Title
Applied Sciences
Volume
volume11
Issue
issue1
Publisher
MDPI
Start Page
397
ISSN
2076-3417
Content Type
Journal Article
language
English
OAI-PMH Set
岡山大学
Copyright Holders
© 2021 by the authors.
File Version
publisher
DOI
Web of Science KeyUT
Related Url
isVersionOf https://doi.org/10.3390/app11010397
License
https://creativecommons.org/licenses/by/4.0/
Funder Name
Japan Society for the Promotion of Science
助成番号
18H03826