基于遗传算法的形态与微气候环境性能自动优化方法  

The Automatic Optimizing Method of Morphological and Microclimatic Environmental Performance Based on Genetic Algorithm

作　　者：刘宇鹏 虞刚[1] 徐小东[1] Liu Yupeng;Yu Gang;Xu Xiaodong

机构地区：[1]东南大学建筑学院

出　　处：《中外建筑》2018年第6期71-74,共4页Chinese & Overseas Architecture

基　　金：国家自然科学基金(51678127);“北京未来城市设计高精尖创新中心——城市设计理论方法体系研究”(UDC2016010100);中国博士后科学基金面上项目(2016M590399);江苏省博士后科研(1601250C);国家留学基金委(CSC#201706095035)资助

摘　　要：城市微气候与城市形态的关联性研究牵涉多个学科,从建筑学角度出发,现有研究已经证实了城市微气候环境与城市形态要素变化直接相关。但已有的城市形态与微气候关联性研究基本是对单一变量逐个进行分析后的人工耦合与优化,对于城市这一复杂体系来说,这种方法只能给出若干近似判断和较优解,并不能给出一个相对准确的最优解。本文提出一种新的算法体系,基于Grasshopper参数化平台,整合了城市形态生成、微气候性能模拟与搜索寻优三个模块,以人体室外舒适度为优化目标,运用遗传算法进行搜索,通过若干代运算之后得出气候适应性城市形态的最优组合。The correlation researches on urban microclimate and urban morphology involve several academic disciplines. From the architectural perspective, existing researches have already verified the direct correlation between urban microclimatic environment and the change of urban morphological factors. However, existing correlation researches on urban morphology and microclimate are basically artificial coupling and optimization after one-by-one analysis of single variables. For such a complicated system as city, this method can only provide several approximate judgments and better solutions, but cannot give a relatively accurate and the best solution. This paper presents a new algorithmic system. Based on the parameterized platform of Grasshopper, this paper integrates three modules： the generation of urban morphology, the simulation of microclimatic performance and the search for optimum. With the outdoor comfort of human body as its optimization target, this paper applies the genetic algorithm for search, and obtains the optimal combination of climate-adapting urban morphology after several iterative operations.

关 键 词：城市形态 微气候 遗传算法 自动优化 LADYBUG BUTTERFLY GALAPAGOS 

分 类 号：TU-023[建筑科学—建筑理论]