ID | 61346 |
フルテキストURL | |
著者 |
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
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抄録 | 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.
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キーワード | maximal covering location problem
capacitated facility
modularity
multi-period
Lagrangian decomposition heuristic
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発行日 | 2021-01-04
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出版物タイトル |
Applied Sciences
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巻 | 11巻
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号 | 1号
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出版者 | MDPI
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開始ページ | 397
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ISSN | 2076-3417
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資料タイプ |
学術雑誌論文
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言語 |
英語
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OAI-PMH Set |
岡山大学
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著作権者 | © 2021 by the authors.
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論文のバージョン | publisher
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DOI | |
Web of Science KeyUT | |
関連URL | isVersionOf https://doi.org/10.3390/app11010397
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ライセンス | https://creativecommons.org/licenses/by/4.0/
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助成機関名 |
日本学術振興会
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助成番号 | 18H03826
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