Urban and Rural Spatial Planning Method Based on Multi-Agent Particle Swarm Optimization Algorithm

LANG Aifang; LI Muzi; TAO Liang

doi:10.13512/j.hndz.2025.01.18

Abstract：Due to the high complexity of the spatial distribution characteristics and shapes of different land types,it is difficult to determine the importance of the three-level spatial types for the overall spatial layout,resulting in a lower utilization rate of the planned space.To this end,a method for urban and rural spatial planning based on a multi-agent particle swarm optimization algorithm was proposed.According to the classification principle of urban and rural production space,living space,and ecological space,the functional zoning of spatial utilization was de-termined.Based on the transfer characteristics of the production-living-ecological space and the changes in the pro-portion of the three-level spatial types,the importance of the three-level land type to spatial planning was calculat-ed.The fractal dimension of the form of urban and rural spatial utilization was determined.By referring to the re-quirements of urban and rural spatial planning,a function with the highest ecological security,the minimum spa-tial planning cost,and the maximum spatial coordination degree was established.A spatial planning model was constructed by integrating corresponding constraint conditions,and a multi-agent particle swarm optimization algo-rithm was introduced to solve the model.Then,the urban and rural spatial planning strategy was output.The experi-mental results show that after using the proposed method for spatial planning of the study area,the minimum open space ratio is only 0.08%.The spatial pattern of the study area has been effectively utilized,and the spatial utiliza-tion rate has significantly improved,indicating excellent planning performance.