Al-Saadi, S. N., & Al-Jabri, K. S. (2020). Optimization of envelope design for housing in hot climates using a genetic algorithm (GA) computational approach. Journal of Building Engineering, 32, 101712.‏ https://doi.org/10.1016/j.jobe.2020.101712
Bragadin, M. A., Pozzi, L., & Kähkönen, K. (2022). Multi-objective Genetic Algorithm for the Time, Cost, and Quality Trade-Off Analysis in Construction Projects. In Nordic Conference on Construction Economics and Organization (pp. 193-207). Springer International Publishing.‏ https://doi.org/10.1007/978-3-031-25498-7_14 
Bui, D. K., Nguyen, T. N., Ghazlan, A., Ngo, N. T., & Ngo, T. D. (2020). Enhancing building energy efficiency by adaptive façade: A computational optimization approach. Applied Energy, 265, 114797.‏ https://doi.org/10.1016/j.apenergy.2020.114797 
Da Silva, M. A., Garcia, R. D. P., & Carlo, J. C. (2024). Multi-objective optimization algorithms for building performance assessment–A benchmark. International Journal of Architectural Computing. https://doi.org/10.1177/14780771241296263 
Deng, X., He, D., & Qu, L. (2024). A novel hybrid algorithm based on arithmetic optimization algorithm and particle swarm optimization for global optimization problems. Journal of Supercomputing, 80(7), 8857-8897.‏ https://doi.org/10.1007/s11227-023-05773-4 
Duhirwe, P. N., Ngarambe, J., & Yun, G. Y. (2023). Energy-efficient virtual sensor-based deep reinforcement learning control of indoor CO2 in a kindergarten. Frontiers of Architectural Research, 12(2), 394-409.‏ https://doi.org/10.1016/j.foar.2022.10.003 
Feng, X., Chen, Y., Zhang, J., Cho, H., & Shi, X. (2021). Rubik’s Cube Topology Based Particle Swarm Algorithm for Bilevel Building Energy Transaction. In Energy Sustainability (Vol. 84881, p. V001T08A002). American Society of Mechanical Engineers.‏ https://asmedigitalcollection.asme.org/ES/proceedings-abstract/ES2021/V001T08A002/1114919 
Ghaderi Dehkordi, M., & Nedaei Tousi, S. (2024). A Sustainable Framework for Intervention and Heritage-Led Regeneration: A Systematic Review. Bagh-e Nazar, 21(131), 35-48.‏ https://doi.org/10.22034/bagh.2024.399296.5382 
Ghasemi Nasab, M., Moulaii, M., & Pilechiha, P. (2021). Accurate simulation of new glazed facades with emphasis on daylighting and energy optimization (Case study: office building in Hamedan). Sustainable Architecture and Urban Design, 9(2), 175-163. https://doi.org/10.22061/jsaud.2021.7529.1811 
Gonidakis, D. N., Frangedaki, E. I., & Lagaros, N. D. (2024). Optimizing Daylight Performance of Digital Fabricated Adobe Walls. Architecture, 4(3), 515-540.‏ https://doi.org/10.3390/architecture4030028 
Güney, H. (2023). Feature selectionintegrated classifier optimisation algorithm for network intrusion detection. Concurrency and Computation: Practice and Experience, 35(23), e7807.‏ https://doi.org/10.1002/cpe.7807 
Hong, W. K., & Le, T. A. (2023). ANN-based optimized design of doubly reinforced rectangular concrete beams based on multi-objective functions. Journal of Asian Architecture and Building Engineering, 22(3), 1413-1429.‏ https://doi.org/10.1080/13467581.2022.2085720  
Hong, W. K., & Nguyen, D. H. (2023). Pareto frontier for steel-reinforced concrete beam developed based on ANN-based Hong-Lagrange algorithm. Journal of Asian Architecture and Building Engineering, 22(6), 3535-3551.‏ https://doi.org/10.1080/13467581.2023.2193621
Hong, W. K., & Pham, T. D. (2024). An ANN-based Hong-Lagrange algorithm (ANN-based HLA) for auto design-based building application (ABBA) with prestressed precast piperack frame. Journal of Asian Architecture and Building Engineering, 23(2), 649-686.‏ https://doi.org/10.1080/13467581.2023.2244575 
Ikeda, S., & Nagai, T. (2021). A novel optimization method combining metaheuristics and machine learning for daily optimal operations in building energy and storage systems. Applied Energy, 289, 116716.‏ https://doi.org/10.1016/j.apenergy.2021.116716 
Ismail, Z. A. (2024). Machine learning applications for a better demand controlled ventilation system experience in buildings: a review. Open House International, 49(3), 444-467.‏ https://doi.org/10.1108/OHI-03-2023-0065
Khodadadi, A. (2023). A Generative design exploration methodology for integration of structural, environmental, and user agencies in an early design stage. International Journal of Architectural Computing, 21(4), 757-780.‏ https://doi.org/10.1177/14780771231183176
Li, Z., Lin, B., Zheng, S., Liu, Y., Wang, Z., & Dai, J. (2020). A review of operational energy consumption calculation method for urban buildings. In Building Simulation (Vol. 13, pp. 739-751). Tsinghua University Press.‏ https://doi.org/10.1007/s12273-020-0619-0 
Mathebula, N. O., Thango, B. A., & Okojie, D. E. (2024). Particle swarm optimisation algorithm-based renewable energy source management for industrial applications: an oil refinery case study. Energies, 17(16), 3929.‏ https://www.mdpi.com/1996-1073/17/16/3929 
Mohan, P., Neelakandan, S., Mardani, A., Maurya, S., Arulkumar, N., & Thangaraj, K. (2023). Eagle strategy arithmetic optimisation algorithm with optimal deep convolutional forest based fintech application for hyper-automation. Enterprise Information Systems, 17(10), 2188123.‏ https://doi.org/10.1080/17517575.2023.2188123 
Shivaprasad More, P., Saini, B. S., & Sharma, R. K. (2023). Optimisation algorithm in health care: review on the State-of-the-Art models. Journal of Experimental & Theoretical Artificial Intelligence, 1-24.‏ https://doi.org/10.1080/0952813x.2023.2217813
Mousavi, S., Gheibi, M., Wacławek, S., Smith, N. R., Hajiaghaei-Keshteli, M., & Behzadian, K. (2023). Low-energy residential building optimisation for energy and comfort enhancement in semi-arid climate conditions. Energy Conversion and Management, 291, 117264.‏ https://doi.org/10.1016/j.enconman.2023.117264 
Najafi, G. S., Gorji Mahlabani, Y., & Pilechiha, P. (2023). Sensitivity analysis and optimization of building geometry with energy-daylight efficiency approach. Sustainable Architecture and Urban Design, 11(1), 45-58. https://doi.org/10.22061/jsaud.2022.8596.1992
Nouri, L., Taghizadeh, K., & Alaghmandan, M. (2023). Development of algorithmic applications in architecture: a review and analysis of L-systems. Bagh-e Nazar, 19(116), 5-22. https://doi.org/10.22034/bagh.2022.327468.5119
Noorollahi, Y., Barabadi, P., Taherahmadi, J., & Abbasizade, F. (2024). Multi-objective optimization of energy demand and net zero energy building design based on climatic conditions (Case study: Iran). International Journal of Environmental Science and Technology, 1-16.‏ https://doi.org/10.1007/s13762-024-06059-9 
Ogar, V. N., Hussain, S., & Gamage, K. A. (2023). Load frequency control using the particle swarm optimisation algorithm and PID controller for effective monitoring of transmission line. Energies, 16(15), 5748.‏ https://www.mdpi.com/1996-1073/16/15/5748 
Olave, D. C. (2022). From efficiency to exhaustion: computer-aided architecture at the madrid calculation center (1968–1973). Technology Architecture Design, 6(1), 59-67.‏ https://doi.org/10.1080/24751448.2022.2040304 
Omrany, H., Soebarto, V., & Ghaffarianhoseini, A. (2022). Rethinking the concept of building energy rating system in Australia: A pathway to life-cycle net-zero energy building design. Architectural Science Review, 65(1), 42-56.‏ https://doi.org/10.1080/00038628.2021.1911783 
Quang, T. V., & Phuong, N. L. (2024). Using Deep Learning to Optimize HVAC Systems in Residential Buildings. Journal of Green Building, 19(1), 29-50. https://doi.org/10.3992/jgb.19.1.29 
Rabani, M., Madessa, H. B., & Nord, N. (2021). Achieving zero-energy building performance with thermal and visual comfort enhancement through optimization of fenestration, envelope, shading device, and energy supply system. Sustainable Energy Technologies and Assessments, 44, 101020.‏ https://doi.org/10.1016/j.seta.2021.101020 
Rachmawati, T. S. N., Khant, L. P., Lim, J., Lee, J., & Kim, S. (2024). Optimization of lap splice positions for near-zero rebar cutting waste in diaphragm walls using special-length-priority algorithms. Journal of Asian Architecture and Building Engineering, 23(6), 1933-1950.‏ https://doi.org/10.1080/13467581.2023.2278881 
Rahnamayiezekavat, P., Wang, D., Chai, J., Moon, S., Rashidi, M., & Wang, X. (2024). Automated pavement marking integrity assessment using a UAV platform–a test case of public parking. Journal of Asian Architecture and Building Engineering, 1-12.‏ https://doi.org/10.1080/13467581.2024.2329358 
Saffari, A., Zahiri, S. H., & Khishe, M. (2023). Fuzzy whale optimisation algorithm: a new hybrid approach for automatic sonar target recognition. Journal of Experimental & Theoretical Artificial Intelligence, 35(2), 309-325.‏ https://doi.org/10.1080/0952813x.2021.1960639 
Sharma, I., & Kumar, V. (2022). Multi-objective tunicate search optimisation algorithm for numerical problems. International Journal of Intelligent Engineering Informatics, 10(2), 119-144.‏ https://doi.org/10.1504/ijiei.2022.125859 
She, C., Jia, R., Hu, B. N., Zheng, Z. K., Xu, Y. P., & Rodriguez, D. (2021). Life cycle cost and life cycle energy in zero-energy building by multi-objective optimization. Energy Reports, 7, 5612-5626.‏ https://doi.org/10.1016/j.egyr.2021.08.198 
Su, C. J., & Zhao, T. (2024). Collaborative optimization of thermal conductivity distribution and heat source layout based on Bayesian optimization. International Journal of Heat and Mass Transfer, 224, 125324.‏ https://doi.org/10.1016/j.ijheatmasstransfer.2024.125324
Tajik, R., Soltanmohammadlou, S., Kianfar, A., Masera, G., & Hoque, S. (2024). A case study: intelligent shading retrofit to existing home-office using multi-objective optimization. Journal of Green Building, 19(1), 123-156. https://doi.org/10.3992/jgb.19.1.123\
Wang, J., Wang, Y., Qiu, D., Su, H., Strbac, G., & Gao, Z. (2025). Resilient energy management of a multi-energy building under low-temperature district heating: A deep reinforcement learning approach. Applied Energy, 378, 124780. https://doi.org/10.1016/j.apenergy.2024.124780 
Wang, A., Xiao, Y., Liu, C., Zhao, Y., & Sun, S. (2024a). Multi-objective optimization of building energy consumption and thermal comfort based on SVR-NSGA-II. Case Studies in Thermal Engineering, 63, 105368. https://doi.org/10.1016/j.csite.2024.105368 
Wang, G., Mukhtar, A., Moayedi, H., Khalilpoor, N., & Tt, Q. (2024b). Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector. Energy, 298, 131312. https://doi.org/10.1016/j.energy.2024.131312 
Wang, Z., Peura, H., & Wiesemann, W. (2024c). Randomized assortment optimization. Operations Research, 72(5), 2042-2060. https://doi.org/10.1287/opre.2022.0129
Wen, Y., Ye, W., & Yu, G. (2024). A Hybrid Multi-Objective Model for Multi-Story Warehouse Design. CAADRIA, 1, 283-292.
Xu, N., Guan, K., & Wang, P. (2024). Improving access to urban parks through public transit optimization. Frontiers of Architectural Research, 13(3), 575-592. https://doi.org/10.1016/j.foar.223.12.011 
Yang, J., Hua, W., Xia, T., Li, Q., Shi, H., & Zhou, X. (2024). Design of Public Rental Settlements Based on Green and Low-Carbon Research: Example of Course Design for a Senior Design Class. Journal of Green Building, 19(2), 133-162. https://doi.org/10.3992/jgb.19.2.133
Yu, K., Bao, Q., Xu, H., Cao, G., & Xia, S. (2024). An extreme learning machine stock price prediction algorithm based on the optimisation of the Crown Porcupine Optimisation Algorithm with an adaptive bandwidth kernel function density estimation algorithm. In Proceedings of the International Conference on Digital Economy, Blockchain and Artificial Intelligence (pp. 116-121). https://doi.org/10.1145/3700058.3700077 
Yue, L., Wang, H., Mumtaz, J., Rauf, M., & Li, Z. (2023). Energy-efficient scheduling of a two-stage flexible printed circuit board flow shop using a hybrid Pareto spider monkey optimisation algorithm. Journal of Industrial Information Integration, 31, 100412. https://doi.org/10.1016/j.jii.2022.100412 
Zhan, X., Zhang, W., Chen, R., Bai, Y., Wang, J., & Deng, G. (2025). Non-dominated sorting genetic algorithm-II: A multi-objective optimization method for building renovations with half-life cycle and economic costs. Building and Environment, 267, 112155. https://doi.org/10.1016/j.buildenv.2024.112155 
Zhang, H., Cui, Y., Cai, H., & Chen, Z. (2024a). Optimization and prediction of office building shading devices for energy, daylight, and view consideration using genetic and BO-LGBM algorithms. Energy and Buildings, 324, 114939. https://doi.org/10.1016/j.enbuild.2024.114939 
Zhang, J., Zheng, H., & Wu, B. (2024b). Multi-objective optimization of distributed photovoltaics on building surfaces from visual impact. Journal of Asian Architecture and Building Engineering, 1-18. https://doi.org/10.1080/13467581.2024.2397097 
Zhang, R., Xu, X., Liu, K., Kong, L., Wang, X., Zhao, L., & Abuduwayiti, A. (2024c). Does architectural design require single-objective or multi-objective optimisation? A critical choice with a comparative study between model-based algorithms and genetic algorithms. Frontiers of Architectural Research, 13(5), 1079-1094. https://doi.org/10.1016/j.foar.2024.03.010
Zhu, Y., Xu, W., Luo, W., Yang, M., Chen, H., & Liu, Y. (2025). Application of hybrid machine learning algorithm in multi-objective optimization of green building energy efficiency. Energy, 316, 133581. https://doi.org/10.1016/j.energy.2024.133581