Optimization Method for Spatial Allocation of Rural Land Use Based on Improved Immune Particle Swarm Optimization Algorithm
LI Muzi
QIN Peishen
SHEN Jiang'ao
Abstract：When solving the spatial allocation optimization model for land use,due to the slow convergence of the algorithm,it is difficult to accurately calculate the individual's movement step,resulting in poor intensive use of land in the study area.Therefore,an optimization method for spatial allocation of rural land use based on an improved immune particle swarm optimization algorithm was proposed.Based on the principles of scientificity,feasibility,sustainable development,and comprehensive coordination,this paper selected the maximizing land use,spatial clustering,and land use benefit as objective functions.By combining land resource utilization and rural development needs,a spatial allocation optimization model for land use was established.Then,corresponding constraints were set on the model,including land area constraints,food security constraints,and land type conversion principle constraints,so as to obtain a comprehensive optimization model.Finally,the immune particle swarm optimization algorithm was used to solve the model,and the individual's movement step was calculated by using chaotic disturbance operators.At the same time,a non-linear decreasing inertia weight factor was introduced to improve the algorithm.The optimal solution of the model was output through iterative operation,and the allocation optimization scheme was obtained.The experimental results show that the proposed method can effectively optimize the spatial allocation of land use in the study area,with intensive land utilization rates higher than 8%,which is superior to the comparison method and has a good application effect.
Keywords：Improved immune particle swarm optimization algorithmSpatial clusteringRural landUtilization spaceAllocation optimization
Publication Date：2025-03-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 152-158 )