多目标微粒群算法用于土地利用空间优化配置

详细信息

A Rural Land Use Spatial Allocation Model Based on Multi-objective Particle Swarm Optimization Algorithm

¹School of Resources and Environmental Science,Wuhan University,129 Luoyu Road,Wuhan 430072,China;²Key Laboratory of Geographic Information System,Ministry of Education,Wuhan University, 129 Luoyu Road,Wuhan 430072,China

摘要: 针对已有空间配置方法在协调土地利用多目标方面的不足,探讨构建基于多目标微粒群算法的土地利用空间优化配置模型。建立了土地利用空间配置方案与单个微粒的映射关系,以经济、社会、生态和综合效益为优化目标,以土地利用优化结构、土地利用现状、地类转换规则为约束条件进行最优配置方案的自组织、智能化搜索,并选取湖北省嘉鱼县作为试验区验证了其有效性。
- 土地利用 /
- 空间优化配置 /
- 微粒群 /
- 多目标优化
Abstract: We present a multi-objective land use spatial allocation model(MOLUSA) based on particle swarm optimization algorithm in order to obtain the optimal spatial land use solution.The model considers economic benefit,social benefit,ecological benefit and spatial compactness as objectives and takes the optimal land use structure,current land use conditions and land use transition rules into account as constraints.We employed the model to reshuffle land use spatial pattern in Jiayu County in Hubei Province of China.
- land use /
- spatial allocation /
- particle swarm optimization /
- multi-objective optimization