王爱英;陈鹏;吴雨婷;王立雄;于娟;
WANG Aiying;CHEN Peng;WU Yuting;WANG Lixiong;YU Juan;Tianjin Key Laboratory of Architectural Physics and Environmental Technology,Tianjin University;

• 1:天津大学天津市建筑物理环境与生态技术重点实验室

摘要(Abstract)：

传统设计优化流程多依赖设计师的大量重复比选,引入启发式算法为实现智能化、自动化优化提供了基础。本文梳理了应用于设计优化的启发式算法及其解决的照明设计优化问题,基于此明确了Revit+Dynamo作为启发式算法应用于照明设计优化的优选实施平台,提出"扩展算法种类、结合照明设计的特点设定算法结构、以参数化方式实现算法的编码和解码、引入效用函数设置约束条件保证算法收敛、将用户主观偏好加入算法评估和更新过程"是启发式算法应用于照明设计优化的改进方向,并据此提出了基于Revit+Dynamo的照明设计优化插件框架。
Traditional design optimization process mostly relies on the repeated comparison and selection by designers. The introduction of heuristic algorithms is the base to realize intelligent and automatic optimization. This article summarizes heuristic algorithms applied to design optimization and the lighting design optimization problem solved. Based on the overview, Revit+Dynamo is identified as the preferred implementation platform for the application of heuristic algorithm to lighting design optimization. And improvement directions for the heuristic algorithms applied to lighting design optimization are expanding kinds of algorithms, setting structure of algorithms in line with characteristics of lighting optimization problem, realizing the encoding and decoding process in a parameterized manner, introducing the utility function into constraint conditions to ensure the convergence of algorithm, and incorporating users' subjective preferences into evaluation and update process. The framework of lighting optimization plug-in on Revit+Dynamo platform is presented according to improvement directions.

关键词(KeyWords)： 启发式算法;照明设计;逆设计;多目标优化;Revit+Dynamo
heuristic algorithm;lighting design;inverse design;multi-objective optimization;Revit+Dynamo

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划(2018YFC0705100);; 国家自然科学基金(51678399);; 天津市研究生科研创新项目(2019YJSB161)

作者(Authors): 王爱英;陈鹏;吴雨婷;王立雄;于娟;
WANG Aiying;CHEN Peng;WU Yuting;WANG Lixiong;YU Juan;Tianjin Key Laboratory of Architectural Physics and Environmental Technology,Tianjin University;

参考文献(References)：

• [1] 罗晓霞.LED照明系统的优化设计[D].长春：中国科学院研究生院(长春光学精密机械与物理研究所),2011.
• [2] 李媛，王书晓，罗涛.书架照明的节能优化设计研究[J].照明工程学报，2015,26(6):7-13.
• [3] 吴思颖.基于视觉舒适度的高校教室夜间照明环境优化研究[D].邯郸：河北工程大学，2020.
• [4] 黄滢滢，林怡，戴奇.节律健康照明的光谱和照明设计优化[J].照明工程学报，2019,30(6):11-17.
• [5] 杨超，程翠，徐一航.基于布灯参数优化的隧道照明节能控制[J].华东交通大学学报，2017,34(2):128-133.
• [6] 岳阳，陈淑燕.基于层次分析法的城市道路照明系统评估与优化[J].中国照明电器，2016(7):5-9.
• [7] 史玲娜，陈伟民，刘显明，等.基于视觉特性的坡路照明节能优化设计[J].灯与照明，2014,38(3):31-35.
• [8] COSTA A,NANNICINI G,SCHROEPFER T,et al.Black-box optimization of lighting simulation in architectural design[C]//Complex Systems Design & Management Asia,Cham:Springer,2015.
• [9] 邹德旋.启发式算法及其在工程优化中的应用[D].沈阳：东北大学，2011.
• [10] GHOLIZADEH S,FATTAHI F.Design optimization of tall steel buildings by a modified particle swarm algorithm[J].The Structural Design of Tall and Special Buildings,2014,23(4):285-301.
• [11] 罗毅.基于参数化设计平台的建筑性能优化流程研究[D].天津：天津大学，2018.
• [12] 魏力恺，张颀，张静远，等.C-Sign:基于遗传算法的建筑布局进化[J].建筑学报，2013(S1):28-33.
• [13] 丹·西蒙.进化优化算法基于仿生和种群的计算机智能方法[M].陈曦，译.北京：清华大学出版社，2018.
• [14] DE SOUSA F L,RAMOS F M,PAGLIONE P,et al.New stochastic algorithm for design optimization[J].AIAA Journal,2003,41(9):1808-1818.
• [15] HANSEN P,MLADENOVIC N.Variable neighborhood search:principles and applications[J].European Journal of Operational Research,2001,130(3):449-467.
• [16] DE CASTRO L N,TIMMIS J I.Artificial immune systems as a novel soft computing paradigm[J].Soft Computing-A Fusion of Foundations,Methodologies and Applications,2003,7(8):526-544.
• [17] YANG X S,DEB S.Cuckoo Search via Lévy Flights[C]// Proceedings of world congress on nature and biologically inspired computing (NaBIC 2009),Piscataway,USA:IEEE,2009.
• [18] DEB K,JAIN H.An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach,part I:solving problems with box constraints[J].IEEE Transactions on Evolutionary Computation,2014,18(4):577-601.
• [19] ZHANG Q F,LI H.MOEA/D:a multiobjective evolutionary algorithm based on decomposition[J].IEEE Transactions on Evolutionary Computation,2007,11(6):712-731.
• [20] SCHOENEMAN C,DORSEY J,SMITS B,et al.Painting with light[C]//Proceedings of the 20th Annual Conference on Computer Graphics and Interactive Techniques,New York:Association for Computing Machinery,1993.
• [21] MATTONI B,GORI P,BISEGNA F.A step towards the optimization of the indoor luminous environment by genetic algorithms[J].Indoor and Built Environment,2017,26(5):590-607.
• [22] RABAZA O,GóMEZ-LORENTE D,POZO A M,et al.Application of a differential evolution algorithm in the design of public lighting installations maximizing energy efficiency[J].LEUKOS,2020,16(3):217-227.
• [23] ERIYADI M,ABDULLAH A G,MULIA S B,et al.Street lighting efficiency with particle swarm optimization algorithm following Indonesian standard[J].Journal of Physics:Conference Series,2019,1402(4):44009.
• [24] MOYLAN K,ROSS B J.Interior illumination design using genetic programming[C]// Evolutionary and Biologically Inspired Music,Sound,Art and Design,Cham:Springer,2015.
• [25] FERNáNDEZ E,BESUIEVSKY G.Inverse lighting design for interior buildings integrating natural and artificial sources[J].Computers & Graphics,2012,36(8):1096-1108.
• [26] LEIRA R,FERNáNDEZ E,BESUIEVSKY G,et al.Calculation of optimal luminaires for architectural design[C]// Proceedings of the 12th International Joint Conference on Computer Vision,Imaging and Computer Graphics Theory and Applications,Setúbal,Portugal:SCITEPress,2017.
• [27] GKARAVELIS A,PAPAIOANNOU G.Inverse lighting design using a coverage optimization strategy[J].The Visual Computer,2016,32(6-8):771-780.
• [28] 黄艳国，宋峰华.遗传蚁群算法在公路隧道照明设计中的应用[J].公路工程，2018,43(4):39-43.
• [29] 豆雨桐，宋佩华，刘畅，等.卧室光源亮度的自动优化算法[J].计算机辅助设计与图形学学报，2020,32(8):1208-1217.
• [30] 韩臻，张颀，刘刚.人工免疫算法在建筑照明改造中的应用[J].照明工程学报，2019,30(2):103-108.
• [31] 栾新源.基于LED可见光通信的室内定位关键技术研究[D].上海：上海大学，2016.
• [32] CORCIONE M,FONTANA L.Optimal design of outdoor lighting systems by genetic algorithms[J].Lighting Research & Technology,2003,35(3):261-277.
• [33] MANDAL P,DEY D,ROY B.Indoor lighting optimization:a comparative study between grid search optimization and particle swarm optimization[J].Journal of Optics,2019,48(3):429-441.
• [34] CASSOL F,SCHNEIDER P S,FRAN?A F H R,et al.Multi-objective optimization as a new approach to illumination design of interior spaces[J].Building and Environment,2011,46(2):331-338.
• [35] 刘嘉，杨海峰，刘浩学，等.公路隧道出口段亮度优化计算[J].安全与环境学报，2014,14(1):65-68.
• [36] MADIAS E D,KONTAXIS P A,TOPALIS F V.Application of multi-objective genetic algorithms to interior lighting optimization[J].Energy and Buildings,2016,125:66-74.
• [37] PLEBE A,CUTELLO V,PAVONE M.Evolving illumination design following genetic strategies[C]// Proceedings of the 9th International Joint Conference on Computational Intelligence,Setúbal,Portugal:SciTePress,2017.
• [38] VILLA C,LABAYRADE R.Multi-objective optimisation of lighting installations taking into account user preferences-a pilot study[J].Lighting Research & Technology,2013,45(2):176-196.
• [39] 彭玲，肖辉.基于NSGA-II的城市隧道照明优化设计[J].照明工程学报，2018,29(2):65-68.
• [40] WOLPERT D H,MACREADY W G.No free lunch theorems for optimization[J].IEEE Transactions on Evolutionary Computation,1997,1(1):67-82.
• [41] UTO.Geco[EB/OL].(2017-10-02)[2020-11-1].https://www.food4rhino.com/app/geco.
• [42] ROUDSARI M S.Ladybug Tools | Home [EB/OL].(2020-11-10)[2020-11-25].https://www.ladybug.tools/.
• [43] RUTTEN D.Galapagos-Addon for Grasshopper | Grasshopper Docs[EB/OL].(2019-12-15)[2020-11-25].https://grasshopperdocs.com/addons/galapagos.html.
• [44] VIERLINGER R.Octopus[EB/OL].(2018-12-05)[2020-11-25].https://www.food4rhino.com/app/octopus.
• [45] 陈航.基于多目标优化算法的寒冷地区办公建筑窗口设计研究[D].天津：天津大学，2017.
• [46] CHANG M,SHIH S.A hybrid approach of dynamic programming and genetic algorithm for multi-criteria optimization on sustainable architecture design[J].Computer-Aided Design and Applications,2014,12(3):310-319.
• [47] RAHMANI ASL M,ZARRINMEHR S,BERGIN M,et al.BPOpt:a framework for BIM-based performance optimization[J].Energy & Buildings,2015,108:401-412.
• [48] 曹宁.粒子群算法在参数化BIM模型优化中的应用研究[D].天津：天津大学，2018.
• [49] 胡启阳.线性规划算法在参数化BIM模型优化中的应用[D].天津：天津大学，2018.
• [50] PLEBE A,CUTELLO V,PAVONE M.Optimizing costs and quality of interior lighting by genetic algorithm[C]// Computational Intelligence 829.Cham:Springer,2019.
• [51] CICHOCKA J M,BROWNE W N,RODRIGUEZ E.Optimization in the architectural practice an international survey[C]// Protocols,Flows and Glitches,Proceedings of the 22nd International Conference of the Association for Computer-Aided Architectural Design Research in Asia,Hong Kong:The Association for Computer-Aided Architectural Design Research in Asia,2017.
• [52] WORTMANN T,WAIBEL C,NANNICINI G,et al.Are genetic algorithms really the best choice for building energy optimization?[C]// Proceedings of the Symposium on Simulation for Architecture & Urban Design.San Diego,USA:The Society for Modeling and Simulation International,2017.
• [53] CHAND S,WAGNER M.Evolutionary many-objective optimization:a quick-start guide[J].Surveys in Operations Research and Management Science,2015,20(2):35-42.
• [54] 周太明，许敏，李福生，等.照明设计从传统光源到LED[M].上海：复旦大学出版社，2015.