This research demonstrates improved land allocation in Chongqing using a co-evolutionary particle swarm optimization algorithm, highlighting its effectiveness.
Rational planning and layout of land types in urban and rural areas can realize the rational use of resources. This paper briefly introduces the optimization model of land allocation for urban and rural planning and uses a particle swarm optimization (PSO) algorithm to solve the land allocation scheme. At the same time, co-evolution was introduced into the PSO algorithm to improve its optimization performance. Then, Chongqing city was taken as an example to optimize the land allocation scheme. The results showed that the three algorithms optimized the land allocation scheme, and the improved PSO algorithm had the best optimization effect. In conclusion, the PSO algorithm optimized by the co-evolution concept can effectively optimize land allocation schemes.
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He et al. (2025) studied this question.
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