Abstract
BackgroundThe residential care system is rapidly developing and plays an increasingly important role in care for the elderly in Beijing. A noticeable disparity in the accessibility to existing residential care facilities, however, is demonstrated in existing studies. The spatial optimization of residential care facility (RCF) locations is urgently needed to promote equal access to residential care resources among the elderly population.MethodsA two-step floating catchment area method with an additional distance-decay function is adopted to measure accessibility to residential care facilities. The spatial optimization model is developed to maximize equity in accessibility by minimizing the total square difference between the accessibility score of each demand location and the weighted average accessibility score. The Particle Swarm Optimization (PSO) method is implemented for the solution.ResultsThe optimized RCF layouts improve equal spatial access to residential care resources with very low accessibility standard variation (0.0066). A relatively large number of beds (51% of the total beds) to be located in the suburban districts between the central and periphery districts of Beijing are optimized. A smaller number of beds to be located in the central and periphery districts (33% and 16% respectively) are optimized. The gaps between the existing and optimized layouts suggest that more RCF beds (5961 beds) are needed in suburban districts, while the RCF beds in some subdistricts located in the central and periphery districts are oversupplied (5253 and 1584 surplus beds respectively).ConclusionsThe optimized results correspond to the municipal special plan proposed by the Beijing government. The optimization objective of this study is different from traditional facility location optimization models, and the method is efficient in maximizing equal access to residential care facilities. This method can support knowledge-based policy-making and planning of residential care facilities.
Highlights
Introduction to the Particle Swarm Optimization Approach (PSO)The PSO is an optimization algorithm originally proposed by Kennedy and Eberhart [32], analogous to the foraging behavior of birds flocking together
Discussions and conclusions This paper first measures the accessibility to residential care facility (RCF) at the subdistrict level in Beijing
The optimal results show that more RCF beds (34,762 beds, 51% of the total) should be allocated to the suburban districts, and less in the central and periphery districts (22,413 and 11,262 beds, 33% and 16% of the total, respectively)
Summary
Introduction to the PSOThe PSO is an optimization algorithm originally proposed by Kennedy and Eberhart [32], analogous to the foraging behavior of birds flocking together. The PSO characterizes a population as m particles and potential solutions. The residential care system is rapidly developing and plays an increasingly important role in care for the elderly in Beijing. The spatial optimization of residential care facility (RCF) locations is urgently needed to promote equal access to residential care resources among the elderly population. A residential care system is rapidly developing and will play an increasingly important role in care for the elderly population in the future [3,4,5,6,7]. The Beijing local government has issued its first municipal special plan for the residential care system, which aims to provide residential care services for four percent of the elderly population in Beijing by 2020 [9]. There is still a large gap between this policy goal and the existing residential care resources in Beijing. To reach the policy goal, another 10,000 beds need to be added per year to the existing stock of beds from 2014 to 2020
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