License: 
Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GIScience.2023.19
URN: urn:nbn:de:0030-drops-189144
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18914/
Chen, Huanfa ;
Xu, Rongbo
Achieving Least Relocation of Existing Facilities in Spatial Optimisation: A Bi-Objective Model (Short Paper)
Abstract
Spatial optimisation models have been widely used to support locational decision making of public service systems (e.g. hospitals, fire stations), such as selecting the optimal locations to maximise the coverage. These service systems are generally the product of long-term evolution, and there usually are existing facilities in the system. These existing facilities should not be neglected or relocated without careful consideration as they have financial or management implications. However, spatial optimisation models that account for the relocation or maintenance of existing facilities are understudied. In this study, we revisit a planning scenario where two objectives are adopted, including the minimum number of sites selected and the least relocation of existing facilities. We propose and discuss three different approaches that can achieve these two objectives. This model and the three approaches are applied to two case studies of optimising the retail stores in San Francisco and the large-scale COVID-19 vaccination network in England. The implications of this model and the efficiency of these approaches are discussed.
BibTeX - Entry
@InProceedings{chen_et_al:LIPIcs.GIScience.2023.19,
author = {Chen, Huanfa and Xu, Rongbo},
title = {{Achieving Least Relocation of Existing Facilities in Spatial Optimisation: A Bi-Objective Model}},
booktitle = {12th International Conference on Geographic Information Science (GIScience 2023)},
pages = {19:1--19:5},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-288-4},
ISSN = {1868-8969},
year = {2023},
volume = {277},
editor = {Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2023/18914},
URN = {urn:nbn:de:0030-drops-189144},
doi = {10.4230/LIPIcs.GIScience.2023.19},
annote = {Keywords: spatial optimisation, location set cover problem, multiple objective}
}
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Keywords: |
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spatial optimisation, location set cover problem, multiple objective |
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Collection: |
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12th International Conference on Geographic Information Science (GIScience 2023) |
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Issue Date: |
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2023 |
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Date of publication: |
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07.09.2023 |
