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Spatial Optimization of Residential Care Facility Configuration Based on the Integration of Modified Immune Algorithm and GIS: A Case Study of Jing’an District in Shanghai, China

Author

Listed:
  • Min Cheng

    (Department of Management Science and Engineering, School of Management, Shanghai University, Shanghai 201900, China)

  • Xiao Cui

    (Department of Construction Management and Real Estate, School of Economics & Management, Tongji University, Shanghai 200092, China)

Abstract

As the population is aging rapidly, the irrationality of residential care facility (RCF) configuration has impacted the efficiency and quality of the aged care services so significantly that the optimization of RCF configuration is urgently required. A multi-objective spatial optimization model for the RCF configuration is developed by considering the demands of three stakeholders, including the government, the elderly, and the investor. A modified immune algorithm (MIA) is implemented to find the optimal solutions, and the geographic information system (GIS) is used to extract information on spatial relationships and visually display optimization results. Jing’an District, part of Shanghai, China, is analyzed as a case study to demonstrate the advantages of this integrated approach. The configuration rationality of existing residential care facilities (RCFs) is analyzed, and a detailed recommendation for optimization is proposed. The results indicate that the number of existing RCFs is deficient; the locations of some RCFs are unreasonable, and there is a large gap between the service supply of existing RCFs and the demands of the elderly. To fully meet the care demands of the elderly, 6 new facilities containing 1193 beds are needed to be added. In comparison with the optimization results of other algorithms, MIA is superior in terms of the calculation accuracy and convergence rate. Based on the integration of MIA and GIS, the quantity, locations, and scale of RCFs can be optimized simultaneously, effectively, and comprehensively. The optimization scheme has improved the equity and efficiency of RCF configuration, increased the profits of investors, and reduced the travel costs of the elderly. The proposed method and optimization results have reference value for policy-making and planning of RCFs as well as other public service facilities.

Suggested Citation

  • Min Cheng & Xiao Cui, 2020. "Spatial Optimization of Residential Care Facility Configuration Based on the Integration of Modified Immune Algorithm and GIS: A Case Study of Jing’an District in Shanghai, China," IJERPH, MDPI, vol. 17(21), pages 1-20, November.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:21:p:8090-:d:439241
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    References listed on IDEAS

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    1. Arif Wismadi & Mark Zuidgeest & Mark Brussel & Martin Maarseveen, 2014. "Spatial Preference Modelling for equitable infrastructure provision: an application of Sen’s Capability Approach," Journal of Geographical Systems, Springer, vol. 16(1), pages 19-48, January.
    2. Tatsuya Nishino, 2017. "Quantitative Properties of the Macro Supply and Demand Structure for Care Facilities for Elderly in Japan," IJERPH, MDPI, vol. 14(12), pages 1-22, December.
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    Cited by:

    1. Zhenwei Wang & Xiaochun Wang & Zijin Dong & Lisan Li & Wangjun Li & Shicheng Li, 2023. "More Urban Elderly Care Facilities Should Be Placed in Densely Populated Areas for an Aging Wuhan of China," Land, MDPI, vol. 12(1), pages 1-13, January.

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