Climate-responsive optimization of building envelope and courtyard proportions across Iran’s diverse climates: A multi-objective NSGA-II framework

  • Leila Sadat Hamidian Divkolaei orcid

    Department of Architecture and Urban Planning, Faculty of Civil Engineering and Architecture, Technical and Vocational University (TVU), Tehran 1435761137, Iran
Article ID: 4259
DOI: https://doi.org/10.59400/be4259
Keywords: building envelope, courtyard design, multi-objective optimization, NSGA-II, energy use intensity, Iran, ladybug tools, honeybee

Abstract

Buildings account for a substantial share of global energy use and greenhouse gas emissions, making climate-responsive envelope design a critical pathway for reducing operational energy demand—particularly in multi-climate countries such as Iran. This study proposes a multi-objective optimization framework that integrates building envelope proportions and courtyard configurations to reduce energy consumption while improving climate-appropriate solar performance. The built-to-open ratio—defined as the proportion of built footprint area relative to total plot area—is the primary geometric variable under investigation. Eight representative historical residential buildings from major Iranian climatic zones (very cold to very hot–humid) were parametrically modeled in Rhino–Grasshopper and evaluated through simulation workflows using Ladybug and Honeybee (EnergyPlus). The optimization process employed the NSGA-II algorithm via Wallacei-X to minimize Energy Use Intensity (EUI, kWh/m2·year) while simultaneously addressing climate-conditioned solar objectives: maximizing incident solar radiation in heating-dominant climates and minimizing solar exposure in cooling-dominant climates on representative extreme days. Results demonstrate a strong climate-dependent relationship between built-to-open ratios and energy performance: in hot climates, higher built-to-open ratios (up to ~80%) substantially decrease EUI, whereas this parameter shows limited influence in moderate and cold climates. The Ahvaz case reveals that single geometric parameters are insufficient under extreme heat conditions, highlighting the need for multi-variable strategies. The findings confirm that combining vernacular courtyard principles with computational optimization yields climate-specific guidance for early-stage envelope design in multi-climate regions.

Published
2026-06-30
How to Cite
Divkolaei, L. S. H. (2026). Climate-responsive optimization of building envelope and courtyard proportions across Iran’s diverse climates: A multi-objective NSGA-II framework. Building Engineering, 4(2). https://doi.org/10.59400/be4259
Issue
Vol. 4 No. 2 (2026)
Section
Article

Copyright (c) 2026 Leila Sadat Hamidian Divkolaei

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

[1]Talaei M, Sangin H. Multi-objective optimization of energy and daylight performance for school envelopes in desert, semi-arid, and mediterranean climates of Iran. Building and Environment. 2024; 255: 111424. doi: 10.1016/j.buildenv.2024.111424

[2]Shahsavari-Pour N, Heydari A, Keynia F, et al. Building electrical consumption patterns forecasting based on a novel hybrid deep learning model. Results in Engineering. 2025; 26: 104522. doi: 10.1016/j.rineng.2025.104522

[3]Mahdavinejad M, Bazazzadeh H, Mehrvarz F, et al. The impact of facade geometry on visual comfort and energy consumption in an office building in different climates. Energy Reports. 2024; 11: 1–17. doi: 10.1016/j.egyr.2023.11.021

[4]Tahmasbi F, Khdair AI, Aburumman GA, et al. Energy-efficient building façades: A comprehensive review of innovative technologies and sustainable strategies. Journal of Building Engineering. 2025; 99: 111643. doi: 10.1016/j.jobe.2024.111643

[5]Hejazi M, Hejazi B, Hejazi S. Evolution of Persian Traditional Architecture Through the History. Journal of Architecture and Urbanism. 2015; 39(3): 188–207. doi: 10.3846/20297955.2015.1088415

[6]Hedayatnia H, Top S, Caluwaerts S, et al. Evaluation of ALARO-0 and REMO Regional Climate Models over Iran Focusing on Building Material Degradation Criteria. Buildings. 2021; 11(8): 376. doi: 10.3390/buildings11080376

[7]European Commission. Defining Zero-Emission Buildings: Support for the Revision of the Energy Performance of Buildings Directive. European Commission; 2023. doi: 10.2760/107493

[8]Voigt MP, Chwalek K, Roth D, et al. The integrated design process of adaptive façades – A comprehensive perspective. Journal of Building Engineering. 2023; 67: 106043. doi: 10.1016/j.jobe.2023.106043

[9]Deng X, Wang M, Sun D, et al. Effect of Building Form on Energy Consumption of Academic Library Buildings in Different Climate Zones in China. IOP Conference Series: Earth and Environmental Science. 2020; 531(1): 012060. doi: 10.1088/1755-1315/531/1/012060

[10]Vukadinović A, Radosavljević J, Đorđević A, et al. Multi-objective optimization of energy performance for a detached residential building with a sunspace using the NSGA-II genetic algorithm. Solar Energy. 2021; 224: 1426–1444. doi: 10.1016/j.solener.2021.06.082

[11]Qiu Z, Yong Q, Wang J, et al. A multi-objective optimization framework for performance-based building design considering the interplay between buildings and urban environments. Energy Conversion and Management. 2024; 315: 118793. doi: 10.1016/j.enconman.2024.118793

[12]Soflaei F, Shokouhian M, Mofidi Shemirani SM. Traditional Iranian courtyards as microclimate modifiers by considering orientation, dimensions, and proportions. Frontiers of Architectural Research. 2016; 5(2): 225–238. doi: 10.1016/j.foar.2016.02.002

[13]Kamelnia H, Hanachi P, Moayedi M. Exploring the spatial structure of Toon historical town courtyard houses: topological characteristics of the courtyard based on a configuration approach. Journal of Cultural Heritage Management and Sustainable Development. 2024; 14(6): 981–997. doi: 10.1108/JCHMSD-03-2022-0051

[14]Shadmand A, Selçuk SA. Lessons from traditional architecture in energy efficient building design: the case of traditional Tabriz houses. International Journal of Environmental Studies. 2022; 79(2): 245–264. doi: 10.1080/00207233.2022.2033492

[15]Akbari H, Joonaghani NNM. Analysis of the geometric and natural properties of courtyards in historical houses of Isfahan (Iran). Journal of Asian Architecture and Building Engineering. 2022; 21(5): 1879–1890. doi: 10.1080/13467581.2021.1971674

[16]Beladi̇ K. Evaluating Sustainability Aspects of Housing in UNESCO world heritage city of Yazd Case Study: Lariha House. AURUM Journal of Engineering Systems and Architecture. 2022; 6(2). doi: 10.53600/ajesa.1139073

[17]McKeen P, Fung A. The Effect of Building Aspect Ratio on Energy Efficiency: A Case Study for Multi-Unit Residential Buildings in Canada. Buildings. 2014; 4(3): 336–354. doi: 10.3390/buildings4030336

[18]Jurshari MZ, Tazakor MY, Yeganeh M. Optimizing the dimensional ratio and orientation of residential buildings in the humid temperate climate to reduce energy consumption (Case: Rasht Iran). Case Studies in Thermal Engineering. 2024; 59: 104484. doi: 10.1016/j.csite.2024.104484

[19]Naghipour P, Naghipour A. Energy performance analysis of residential buildings in Bandar Anzali: Influence of orientation and aspect ratio. Next Sustainability. 2025; 5: 100140. doi: 10.1016/j.nxsust.2025.100140

[20]Zhao Y, Xu Y, Yu M. An approach for measuring and analyzing embodied carbon in the construction industry chain based on emergy accounting. Ecological Indicators. 2024; 158: 111481. doi: 10.1016/j.ecolind.2023.111481

[21]Mahjoub A, Ghomeishi M. Energy Consumption Based on Shape and Orientation in Tehran. Journal of Buildings and Sustaina. 2017; 2(1). Available online: https://www.researchgate.net/publication/327578704_Energy_Consumption_Based_on_Shape_and_Orientation_in_Tehran

[22]El-Agami M, Hanafy G, Osman M. Investigating the Effect of High-Rise Buildings’ Mass Geometry on Energy Efficiency within the Climatic Variation of Egypt. Sustainability. 2021; 13(19): 10529. doi: 10.3390/su131910529

[23]Haseeb QS, Yunus SM, Shoshan AAA, et al. A study of the optimal form and orientation for more energy efficiency to mass model multi-storey buildings of Kirkuk city, Iraq. Alexandria Engineering Journal. 2023; 71: 731–741. doi: 10.1016/j.aej.2023.03.020

[24]Asyrafi A, Andrea SD. Passive Design Strategy of Vertical Housing for Optimizing Energy Efficiency. IOP Conference Series: Earth and Environmental Science. 2024; 1404(1): 012014. doi: 10.1088/1755-1315/1404/1/012014

[25]Ekici BB, Yüksel EN. Orhan G. Investigation of the Performance of Shading Elements in Different Climate Zones. In: Space in Macro and Micro Scales. Livre de Lyon; 2022. pp. 157–171.

[26]Gassar AAA, Jafar R. Artificial Intelligence-Enabled Heating, Ventilation, and Air Conditioning Systems Toward Zero-Emission Buildings: A Systematic Review of Applications, Challenges, and Future Directions. Applied Sciences. 2025; 15(19): 10497. doi: 10.3390/app151910497

[27]Nagaraju D, Mendu SS, Chinta ND. A numerical approach to design building envelope for energy efficient building. International Journal on Interactive Design and Manufacturing (IJIDeM). 2025; 19(1): 199–218. doi: 10.1007/s12008-023-01636-7

[28]Al-Yasiri Q, Szabó M. Incorporation of phase change materials into building envelope for thermal comfort and energy saving: A comprehensive analysis. Journal of Building Engineering. 2021; 36: 102122. doi: 10.1016/j.jobe.2020.102122

[29]Xiang J, Liu H, Li X, et al. Multi-Objective Optimization of Ultra-Low Energy Housing in Hot Summer Cold Winter Climate Zone of China Based on a Probabilistic Behavioral Model. Buildings. 2023; 13(5): 1172. doi: 10.3390/buildings13051172

[30]Kabiri E, Maftouni N. Multiple objective energy optimization of a trade center building based on genetic algorithm using ecological materials. Scientific Reports. 2024; 14(1): 9366. doi: 10.1038/s41598-024-58515-8

[31]Zou Y, Lou S, Xia D, et al. Multi-objective building design optimization considering the effects of long-term climate change. Journal of Building Engineering. 2021; 44: 102904. doi: 10.1016/j.jobe.2021.102904

[32]Lahmar S, Maalmi M, Idchabani R. Multiobjective building design optimization using an efficient adaptive Kriging metamodel. SIMULATION. 2025; 101(5): 557–573. doi: 10.1177/00375497231168630

[33]Xu X, Li X. Construction of Building an Energy Saving Optimization Model Based on Genetic Algorithm: International Journal of Information Technologies and Systems Approach. 2023; 16(3): 1–15. doi: 10.4018/IJITSA.328758

[34]Kiss B, Szalay Z. Modular approach to multi-objective environmental optimization of buildings. Automation in Construction. 2020; 111: 103044. doi: 10.1016/j.autcon.2019.103044

[35]Kiss BG. Multi-Objective Environmental Optimization of Buildings [PhD Thesis]. Budapest University of Technology and Economics; 2022. Available online: https://repozitorium.omikk.bme.hu/server/api/core/bitstreams/b48ac044-85dd-438d-a0db-5c598cfce2a4/content

[36]Baboli FBM, Ibrahim N, Sharif DM. Design Characteristics and Adaptive Role of the Traditional Courtyard Houses in the Moderate Climate of Iran. Procedia - Social and Behavioral Sciences. 2015; 201: 213–223. doi: 10.1016/j.sbspro.2015.08.170

[37]Eltrapolsi A, Mahmoud K, Altan H. A Review of the Geometric Proportions of Shaping a Courtyard of Traditional Architecture in Relation to Human Scale, Tripoli, Libya. Heritage. 2022; 5(3): 2282–2297. doi: 10.3390/heritage5030119

[38]Taleghani M, Tenpierik M, Van Den Dobbelsteen A. Energy performance and thermal comfort of courtyard/atrium dwellings in the Netherlands in the light of climate change. Renewable Energy. 2014; 63: 486–497. doi: 10.1016/j.renene.2013.09.028

[39]Fang Y, Cho S. Design optimization of building geometry and fenestration for daylighting and energy performance. Solar Energy. 2019; 191: 7–18. doi: 10.1016/j.solener.2019.08.039

[40]Wang S, Yi YK, Liu N. Multi-objective optimization (MOO) for high-rise residential buildings’ layout centered on daylight, visual, and outdoor thermal metrics in China. Building and Environment. 2021; 205: 108263. doi: 10.1016/j.buildenv.2021.108263

[41]Idrissi YC, Belarbi R, Ferroukhi MY, et al. Development of a numerical approach to assess the effect of coupled heat and moisture transfer on energy consumption of residential buildings in Moroccan context. Journal of Building Physics. 2022; 45(6): 774–808. doi: 10.1177/17442591211056068

[42]Liu K, Xu X, Huang W, et al. A multi-objective optimization framework for designing urban block forms considering daylight, energy consumption, and photovoltaic energy potential. Building and Environment. 2023; 242: 110585. doi: 10.1016/j.buildenv.2023.110585

[43]Heydaripour O, Del TT. Energy Performance Modeling of Residential Isfahan Apartments Based on Geometric Characteristics. Geographical Research. 2024; 39(3): 299–308. Available online: https://georesearch.ir/browse.php?a_id=1634&sid=1&slc_lang=en&html=1

[44]Gholami H, Kamelnia H, Mahdavinejad MJ, et al. Optimizing Building Configuration and Orientation for Social Housing Projects in Iran. Iranica Journal of Energy and Environment. 2025; 16(2): 289–308. doi: 10.5829/ijee.2025.16.02.11

[45]Turrin M, Von Buelow P, Stouffs R. Design explorations of performance driven geometry in architectural design using parametric modeling and genetic algorithms. Advanced Engineering Informatics. 2011; 25(4): 656–675. doi: 10.1016/j.aei.2011.07.009

[46]Fonseca JA, Nguyen TA, Schlueter A, et al. City Energy Analyst (CEA): Integrated framework for analysis and optimization of building energy systems in neighborhoods and city districts. Energy and Buildings. 2016; 113: 202–226. doi: 10.1016/j.enbuild.2015.11.055

[47]Nasrollahzadeh N. Comprehensive building envelope optimization: Improving energy, daylight, and thermal comfort performance of the dwelling unit. Journal of Building Engineering. 2021; 44: 103418. doi: 10.1016/j.jobe.2021.103418

[48]Esfahankalateh AT, Farrokhzad M, Saberi O, et al. Achieving wind comfort through window design in residential buildings in cold climates, a case study in Tabriz city. International Journal of Low-Carbon Technologies. 2021; 16(2): 502–517. doi: 10.1093/ijlct/ctaa082

[49]Najafi MS, Alizadeh O. Climate zones in Iran. Meteorological Applications. 2023; 30(5): e2147. doi: 10.1002/met.2147

[50]Oskouei EA, Khaki BD, Kouzegaran S, et al. Mapping Climate Zones of Iran Using Hybrid Interpolation Methods. Remote Sensing. 2022; 14(11): 2632. doi: 10.3390/rs14112632

[51]Motealleh P, Zolfaghari M, Parsaee M. Investigating climate responsive solutions in vernacular architecture of Bushehr city. HBRC Journal. 2018; 14(2): 215–223. doi: 10.1016/j.hbrcj.2016.08.001

[52]Heidari S, Ghafari SG. Determining thermal Comfort Period for Tabriz. ReasearchGate; 2011. Available online: https://www.researchgate.net/publication/312317699_Determining_Thermal_Comfort_Period_for_Tabriz

[53]Shaeri J, Yaghoubi M, Aflaki A, et al. Evaluation of Thermal Comfort in Traditional Houses in a Tropical Climate. Buildings. 2018; 8(9): 126. doi: 10.3390/buildings8090126

[54]Heidari AA, Ghasemian AA, Kiai M. Analysis of spatial structure of traditional Iranian houses using spatial syntax method Case study: Comparison of Yazd, Kashan and Isfahan houses. Islamic Iranian City Studies. 2017; 7(28): 21–33.

[55]Liu Y, Wang W, Li Z, et al. Daylighting Performance and Thermal Comfort Performance Analysis of West-Facing External Shading for School Office Buildings in Cold and Severe Cold Regions of China. Sustainability. 2023; 15(19): 14458. doi: 10.3390/su151914458

[56]Ehrgott M. Vilfredo Pareto and multi-objective optimization. In: Documenta Mathematica Series. EMS Press; 2012. pp. 447–453. doi: 10.4171/dms/6/43

[57]Bekdaş G, Aydın Y, Isıkdağ Ü, et al. Prediction of Cooling Load of Tropical Buildings with Machine Learning. Sustainability. 2023; 15(11): 9061. doi: 10.3390/su15119061

[58]Shao T, Wang J, Wang R, et al. Multi-Objective Optimization for the Energy, Economic, and Environmental Performance of High-Rise Residential Buildings in Areas of Northwestern China with Different Solar Radiation. Applied Sciences. 2024; 14(15): 6719. doi: 10.3390/app14156719