A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as Hong Kong

Public health-care facilities are essential to all communities, and their location/allocation has long been an important issue in urban planning. Given the steady growth of Hong Kong's population, new health-care facilities will need to be built over the next few years. This research examines t...

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Main Authors: ZHANG, Wenting, CAO, Kai, LIU, Shaobu, HUANG, Bo
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Language:English
Published: Institutional Knowledge at Singapore Management University 2016
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Online Access:https://ink.library.smu.edu.sg/sis_research/5418
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6421&context=sis_research
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spelling sg-smu-ink.sis_research-64212020-12-11T06:25:42Z A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as Hong Kong ZHANG, Wenting CAO, Kai LIU, Shaobu HUANG, Bo Public health-care facilities are essential to all communities, and their location/allocation has long been an important issue in urban planning. Given the steady growth of Hong Kong's population, new health-care facilities will need to be built over the next few years. This research examines the problem of where such health-care facilities should be located to improve the equity of accessibility, raise the total accessibility for the entire population, reduce the population that falls outside the coverage range, and decrease the cost of building new facilities. However, because urban areas such as Hong Kong are complex socio-ecological systems, the aforementioned conflicting objectives make it impossible to find one ‘best’ solution that meets all of the objectives. Therefore, this research uses a genetic algorithm based multi-objective optimization (MOO) approach to yield a set of Pareto solutions that can be used to find the most practical tradeoffs between the conflicting objectives. The MOO approach is used to optimize the location of new health-care facilities in Hong Kong for 2020. Because the MOO approach provides a set of diverse plans, planners can compare the value of each objective and the spatial distribution of facilities to analyze or select the solution that best supports their further decisions. Comparing the Pareto solutions with other solutions, it indicates that the MOO approach is a sensible choice for solving multi-objective problems of health-care facility location-allocation in Hong Kong. 2016-09-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5418 https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6421&context=sis_research http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Health-care facility Location-allocation problem Multi-objective optimization Hong Kong Asian Studies Databases and Information Systems Health Information Technology
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Health-care facility
Location-allocation problem
Multi-objective optimization
Hong Kong
Asian Studies
Databases and Information Systems
Health Information Technology
spellingShingle Health-care facility
Location-allocation problem
Multi-objective optimization
Hong Kong
Asian Studies
Databases and Information Systems
Health Information Technology
ZHANG, Wenting
CAO, Kai
LIU, Shaobu
HUANG, Bo
A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as Hong Kong
description Public health-care facilities are essential to all communities, and their location/allocation has long been an important issue in urban planning. Given the steady growth of Hong Kong's population, new health-care facilities will need to be built over the next few years. This research examines the problem of where such health-care facilities should be located to improve the equity of accessibility, raise the total accessibility for the entire population, reduce the population that falls outside the coverage range, and decrease the cost of building new facilities. However, because urban areas such as Hong Kong are complex socio-ecological systems, the aforementioned conflicting objectives make it impossible to find one ‘best’ solution that meets all of the objectives. Therefore, this research uses a genetic algorithm based multi-objective optimization (MOO) approach to yield a set of Pareto solutions that can be used to find the most practical tradeoffs between the conflicting objectives. The MOO approach is used to optimize the location of new health-care facilities in Hong Kong for 2020. Because the MOO approach provides a set of diverse plans, planners can compare the value of each objective and the spatial distribution of facilities to analyze or select the solution that best supports their further decisions. Comparing the Pareto solutions with other solutions, it indicates that the MOO approach is a sensible choice for solving multi-objective problems of health-care facility location-allocation in Hong Kong.
format text
author ZHANG, Wenting
CAO, Kai
LIU, Shaobu
HUANG, Bo
author_facet ZHANG, Wenting
CAO, Kai
LIU, Shaobu
HUANG, Bo
author_sort ZHANG, Wenting
title A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as Hong Kong
title_short A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as Hong Kong
title_full A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as Hong Kong
title_fullStr A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as Hong Kong
title_full_unstemmed A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as Hong Kong
title_sort multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as hong kong
publisher Institutional Knowledge at Singapore Management University
publishDate 2016
url https://ink.library.smu.edu.sg/sis_research/5418
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6421&context=sis_research
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