Analysis shows improved accessibility to urban parks in Yanta District, suggesting optimization models may enhance green space planning.
This paper briefly introduces a park green space evaluation model based on supply and demand accessibility, the K-means algorithm for determining the optimal number of new green spaces, and an improved genetic algorithm (GA) for planning these spaces. Moreover, a case study of Yanta District in Xi'an City, China, is presented. The results showed that before optimization, 283 residential areas in Yanta District were in a state where the supply and demand accessibility of green spaces was insufficient. Considering the cost of new green spaces and the average distance from residential areas to these spaces, the final number of new green spaces was set at nine. The improved GA improved the supply and demand accessibility in more residential areas after planning new green spaces.
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Xiaojie Liu (2025) studied this question.
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