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基于可扩展多目标蚁群算法的土地利用优化配置
引用本文:莫致良,杜震洪,张丰,刘仁义.基于可扩展多目标蚁群算法的土地利用优化配置[J].浙江大学学报(理学版),2017,44(6):649.
作者姓名:莫致良  杜震洪  张丰  刘仁义
作者单位:1. 浙江大学 浙江省资源与环境信息系统重点实验室, 浙江 杭州 310028;
2. 浙江大学 地理信息科学研究所, 浙江 杭州 310027
基金项目:国家自然科学基金资助项目(41471313,41101356);浙江省科技攻关计划项目(2013C33051);国家海洋公益性行业科研专项(201505003-6,201305012);国家科技基础性工作专项(2012FY112300);中央高校基本科研业务费专项资金资助项目(2016XZZX004-02).
摘    要:传统的土地利用优化配置模型无法灵活应对现实场景中多变的优化目标要求,也无法实现土地利用在空间布局上的优化.根据常见的优化目标进行抽象建模,建立了可扩展的多目标体系,并与蚁群算法有机结合,构建了基于可扩展多目标蚁群算法的土地利用优化配置模型,使土地利用配置在不同目标的指导下能够灵活优化,同时实现了土地利用配置在数量结构和空间布局优化上的统一,为土地利用规划提供了更具现实意义的参考方案.最后对该模型,以杭州市萧山区2015年土地利用格局为基础数据进行实例验证.结果表明:模型能够在多目标体系的指导下,合理配置研究区域的土地利用结构与布局,促进区域土地利用的可持续发展,并针对不同的多目标体系,给出具有不同侧重点的优化方案.

关 键 词:土地利用优化配置  蚁群算法  可扩展的多目标体系  
收稿时间:2017-08-10

Landuse optimizing allocation based on extensible multi-objective ant colony algorithm
MO Zhiliang,DU Zhenhong,ZHANG Feng,LIU Renyi.Landuse optimizing allocation based on extensible multi-objective ant colony algorithm[J].Journal of Zhejiang University(Sciences Edition),2017,44(6):649.
Authors:MO Zhiliang  DU Zhenhong  ZHANG Feng  LIU Renyi
Institution:1. Zhejiang Provincial Key Lab of GIS, Zhejiang University, Hangzhou 310028, China;
2. Department of Geographic Information Science, Zhejiang University, Hangzhou 310027, China
Abstract:The traditional land use optimizing allocation model can't flexibly response to the changing optimizing requirements under the realities, and can't achieve the optimization of land use in spatial layout. This paper abstracts modeling based on the common optimizing targets, and establishes an extensible multi-objective system combining with the ant colony algorithm. Finally, a land use optimizing allocation model based on extensible multi-objective ant colony algorithm is constructed, making the land use optimizing allocation more flexible under the direction of different multi-objective systems, realizing the unification of land use optimizing allocation in structure and spatial layout, and providing a more practical reference for land use planning. The Xiaoshan district of Hangzhou is an area of good economic, social and ecological environment, which makes it a good choice of our study area to verify the model. The experimental results show that the model can reasonably allocate the land use layout of the study area under the guidance of multi-objective system, promote the sustainable development of regional land use, and give different optimization schemes for different multi-objective systems.
Keywords:land use optimizing allocation  ant colony algorithm  extensible multi-objective system
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