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

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.

Towards an understanding of inequalities in accessing residential and nursing home provision: The role of geographical approaches

“…Their supply/demand analysis enabled the identification of disparities in the availability of such services but as acknowledged by the researchers, used relatively simplistic service ratios of beds per total population for specified cultural groups for census tracts whose geometric centroid was within 2 km walking distance of residential care facilities. Other approaches have integrated GIS functionality and map visualisation with optimisation models to identify the impacts of alternative spatial configurations of residential care facilities and inform policy makers where more homes of sufficient capacity are required to meet potential demand (Cheng & Cui, 2020 ). The types of approach described in this paper have the potential to build on these approaches, estimating access to residential care homes by including supply‐side (number of beds within residential care homes) and demand‐side (populations within specified age‐cohorts) parameters at more detailed spatial scales.…”

“…Other approaches have integrated GIS functionality and map visualisation with optimisation models to identify the impacts of alternative spatial configurations of residential care facilities and inform policy makers where more homes of sufficient capacity are required to meet potential demand (Cheng & Cui, 2020). The types of approach described in this paper have the potential to build on these approaches, estimating access to residential care homes by including supply-side (number of beds within residential care homes) and demand-side (populations within specified age-cohorts) parameters at more detailed spatial scales.…”

Analysis of Location Selection of Public Service Facilities Based on Urban Land Accessibility

“…Song et al [ 7 ] utilized the new gravity P-median model to conduct an empirical study for the spatial equilibrium layout of general hospitals in the urban area of Nanjing City. Cheng et al [ 8 ] implemented a modified immune algorithm (MIA) to find the optimal solutions for placing residential care facilities.…”

Spatial-temporal analysis of urban-rural differences in the development of elderly care institutions in China

“…Fourth, community-scale spatial-temporal analysis. GIS technology is used to analyses the spatial distribution of elderly institutions at the community scale, to solve the accuracy of the spatial allocation of elderly institutions, and to provide countermeasure suggestions for community-based home care (44)(45)(46)(47).…”