基于粒子群算法的城镇土地利用空间优化模型

土地利用结构优化是土地资源优化配置的核心，包括数量结构优化和空间结构优化。针对传统的优化模型如线性规划、多目标、灰色系统和景观生态等不能实现土地数量结构和空间结构的有效统一，在研究现有智能优化模型如元胞自动机、遗传算法的基础上，采用近年来新兴的粒子群优化算法，利用其空间飞行搜索特性和较强的全局优化能力，构建了基于粒子群算法的土地利用空间优化模型。研究表明，该模型能利用粒子的群体空间分布模拟土地利用空间格局，并能在多目标控制下进行全局优化处理，实现土地利用数量结构和空间结构的有效统一。

Model of urban land-use spatial optimization based on particle swarm optimization algorithm

The optimization of land-use structure is the core issue of land use planning, including the optimization of quantity and spatial allocation. The existed optimization models such as multi-objective, linear programming, gray system and landscape ecology, etc., are unable to realize quantitative and spatial optimization simultaneously. This paper created a land use spatial optimization model based on the particle swarm optimization algorithm, which had efficient spatial evolution simulate capabilities and robust algorithm. Case study illustrates that this model could be used to stimulate the landscape pattern and its evolution by designing appropriate spatial distribution pattern of particles group, which could integrate the quantity structure optimization into land use spatial evolution simulation.