基于决策网络和风险约束优化的城市增长边界调控模式研究

项目名称： 基于决策网络和风险约束优化的城市增长边界调控模式研究

项目编号： No.51278526

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 建筑科学

项目作者： 韩昊英

作者单位： 浙江大学

项目金额： 80万元

中文摘要： 如何通过建立科学的城市增长边界调控体系来塑造可持续的城市发展形态，是我国快速城市化进程中城市规划领域亟待解决的重大课题。本项目通过借鉴存货控制的理论，引入土地存量这一概念，界定和比较基于土地存量的城市增长边界调控的几种典型方式，并通过定义和计算土地存量控制的成本，构建土地存量控制的概念模型。同时，将风险约束优化（RCO）和决策网络（DN）等决策及规划分析工具加以改进和整合为，弱化主观预期效用理论（SEU）的作用，并结合考虑风险规避和决策关联，以更有效地应对复杂城市系统的不确定性，进而辅助城市增长边界调控模式的构建与选择。研究综合采用遥感、地理信息科学、案例调查和模型分析等方法，构建土地存量控制的风险约束优化决策网络（RCO/DN）模型，进而探讨适合于未来城市发展的城市增长边界调控模式以及实施该模式的具体途径。本项目研究对于城市用地扩展管理的优化具有重要的理论意义和应用价值。

中文关键词： 城市增长边界；土地存量；复杂；决策网络；风险约束优化

英文摘要： During the rapid urbanization process in China, it has been a crucial issue for urban planning academics to attain sustainable urban forms through scientific control of urban growth boundaries (UGBs). Drawing on the theory of inventory control, this project introduces the concept of “land inventory”. It defines and compares several typical control mechanisms for UGBs and constructs a theoretical model by identifying and calculating the costs of land inventory control. At the same time, it improves and integrates two decision and planning analysis tools, including the risk-constrained optimization (RCO) and decision network (DN), in order to weaken the reliance on subjective expected utility (SEU) and consider both risk avoidance and linked decisions. It can cope more effectively with the uncertainties in the complex urban systems and support planners to construct and select the optimal control models of UGBs. By adopting and integrating many advanced technologies including remote sensing (RS), geographic information system/science (GIS), case studies and modeling, this project designs a RCO/DN model and applies it in land inventory control. It further explores the control model of UGBs and its implementation processes in relation to urban development. This project is of great theoretical and practical importance

英文关键词： urban growth boundaries；land inventory；complexity；decision network；risk-constrained optimization