Genetic Evolutionary Algorithm in Architecture: Analyzing the Methods of Genetic Evolutionary Algorithms in the Process of Reproducing the Aesthetic Values of Architectural Design

Abstract :

This study examines the application of the Genetic Algorithm (GA) in the architectural design process with a focus on reproducing aesthetic values such as balance, proportion, harmony, rhythm, and innovation. In today’s world, where the boundaries between art, science, and technology—especially with the advent of artificial intelligence—are increasingly converging, the use of computational tools like genetic algorithms in architectural design has become an inevitable necessity. The fundamental issue addressed in this paper is the challenge of understanding and reproducing the subjective and aesthetic components in architectural design—concepts that are typically considered intuitively and non-quantitatively in traditional design processes. However, genetic algorithms possess the capability to convert these concepts into measurable and quantifiable parameters that can be input into a computational system in the form of a fitness function. Accordingly, the paper’s hypothesis is that by properly designing chromosomes, defining an appropriate objective function, and applying genetic operators such as mutation and crossover, it is possible to generate forms that embody architectural aesthetic values. The research method is qualitative and based on content analysis. In this approach, the authors analyze seven design case studies based on genetic algorithms, examining various stages of architectural design using this algorithm. These stages include encoding forms as digital chromosomes, defining the objective function based on aesthetic criteria, executing an iterative process of generation production, selecting the best forms, and progressively improving design quality.

References:

• al-Rawi, Ossama MOHAMED (2020) "Origins of Computational Design in Architecture," Future Engineering Journal: Vol. 1 : Iss. 1 , Article 5.
• Arturo Tedeschi (2014), AAD Algorithms-Aided Design, Parametric Strategies usinghttps://en.wikipedia.org/wiki/Genetic_algorithm
• Caldas, L. and Rocha, J. (2001) “A Generative Design System applied to Siza’s School of Architecture at Oporto” in: Proceedings of the Sixth Conference on Computer Aided Architectural Design Research in Asia, Sidney, Australia, pp. 253-264.
• Cohoon, J; et al. (2002-11-26). Evolutionary algorithms for the physical design of VLSI circuits (PDF). Advances in Evolutionary Computing: Theory and Applications. Springer, pp. 683-712, 2003. ISBN 978-3-540-43330-9
• Dapogny, Charles; Faure, Alexis; Michailidis, Georgios; Allaire, Grégoire; Couvelas, Agnes; Estevez, Rafael (2017). "Geometric constraints for shape and topology optimization in architectural design" (PDF). Computational Mechanics. 59 (6): 933–965. Bibcode:2017CompM..59..933D. doi:10.1007/s00466-017-1383-6. S2CID 41570887.
• Driscoll, John Charles, "Fractal Dimension as Objective Function in a Genetic Algorithm for Application in Architectural Design" (2019). Systems Science Friday Noon Seminar Series. 80.
• H. Song, et al., Architectural design of apartment buildings using the Implicit Redundant Representation Genetic Algorithm, Automation in Construction (2016), http://dx.doi.org/10.1016/j.autcon.2016.09.00
• Hung Lo, Chi., Ya-Chuan Ko, Shih-Wen Hsiao (2015), A study that applies aesthetic theory and genetic algorithms to product form optimization, Advanced Engineering Informatics, Volume 29, Issue 3, August 2015, Pages 662-679
• J. Felkner, E. Chatzi and T. Kotnik, "Interactive particle swarm optimization for the architectural design of truss structures," 2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES), 2013, pp. 15- 22, doi: 10.1109/CIES.2013.6611723.
• Kolarevic, B. (2003) Architecture in the Digital Age: Design and Manufacturing, New York: Spon Press.
• Krish, Sivam (2011). "A practical generative design method". Computer-Aided Design. 43 (1): 88–100. doi:10.1016/j.cad.2010.09.009
• Li Li,)2012(The optimization of architectural shape based on Genetic Algorithm,Frontiers of Architectural Research,Volume 1, Issue 4,2012,Pages 392-399,ISSN 2095-2635, https://doi.org/10.1016/j.foar.2012.07.005
• Lu, Yingxiu (2018): Conversational Form-Generation: An Application of Interactive Genetic Algorithm to Architectural Design. Carnegie Mellon University. Thesis. https://doi.org/10.1184/R1/7182263.v1
• Maikantis, Theodoros, Angeliki-Agathi Tsintzira, Apostolos Ampatzoglou, Elvira-Maria Arvanitou, Alexander Chatzigeorgiou, Ioannis Stamelos, Stamatia Bibi, and Ignatios Deligiannis (2020), Software Architecture Reconstruction via a Genetic Algorithm: Applying the Move Class Refactoring, Proceedings of the 24th Pan-Hellenic Conference on Informatics, Pages 135 – 139.
• Mars, A., Grabska, E., Ślusarczyk, G., & Strug, B. (2019). Style-Oriented Evolutionary Design of Architectural Forms Directed by Aesthetic Measure. In J. S. Gero (Ed.), Design Computing and Cognition '18 (pp. 629–646). Springer. https://doi.org/10.1007/978-3-030-05363-5_38
• Mars, A., Grabska, E., Ślusarczyk, G., & Strug, B. (2020). Design characteristics and aesthetics in evolutionary design of architectural forms directed by fuzzy evaluation. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 34(2), 147–159. https://doi.org/10.1017/S0890060420000153
• Meintjes, Keith. ""Generative Design" – What's That? - CIMdata". Retrieved 2018-06-15.
• Mitchell, Melanie; Taylor, Charles E (1999). "Evolutionary computation: an overview". Annual Review of Ecology and Systematics. 30 (1): 593–616. doi:10.1146/annurev.ecolsys.30.1.593.
• Papapavlou, A., Turner A., 2009. Structural evolution: a genetic algorithm method to generate structurally optimal delaunay triangulated space frames for dynamic loads. In: 27th eCAADe Conference, Istanbul.
• Prasanta, Rajamoney, Shankar A. Rosenbloom, Paul S.; Wagner, Chris Bose (2014-09-04). Compositional model based design: A generative approach to the conceptual design of physical systems. University of Southern California. OCLC 1003551283
• Schumacher, P. (2016). Parametricism 2.0: Rethinking Architecture's Agenda for the 21st Century. Architectural Design, 86(2), 8–17. https://doi.org/10.1002/ad.2018
• Schwab, K. (2019). How generative design is changing the way architects work. Fast Company.
• Schwab, Katharine (16 April 2019). "This is the first commercial chair made using generative design". Fast Company.
• Schwehr, P. (2011), "Evolutionary Algorithms In Architecture", Open House International, Vol. 36 No. 1, pp. 16-24. https://doi.org/10.1108/OHI-01-2011-B0003
• Shea, Kristina; Aish, Robert; Gourtovaia, Marina (2005). "Towards integrated performance-driven generative design tools". Automation in Construction. 14 (2): 253–264. doi:10.1016/j.autcon.2004.07.002
• Vikhar, P. A. (2016). "Evolutionary algorithms: A critical review and its future prospects". Proceedings of the 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC). Jalgaon: 261–265. doi:10.1109/ICGTSPICC.2016.7955308. ISBN 978-1-5090-0467-6. S2CID 22100336.
• Whitley, Darrell (1994). "A genetic algorithm tutorial" (PDF). Statistics and Computing. 4 (2): 65–85. CiteSeerX 10.1.1.184.3999. doi:10.1007/BF00175354. S2CID 3447126
• Y. Zhang, G. Fei and W. Shang, "3D architecture facade optimization based on genetic algorithm and neural network," 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS), 2017, pp. 693-698, doi: 10.1109/ICIS.2017.7960082. https://en.wikipedia.org/wiki/Genetic_algorithm
Frazer, J. (1995). An Evolutionary Architecture. Architectural Association Publications.
Aish, R., & Woodbury, R. (2005). Multi-level Interaction in Parametric Design. Proceedings of the CAAD Futures Conference.
Oxman, R. (2008). Digital Architecture as a Challenge for Design Pedagogy: Theory, Knowledge, Models and Medium. Design Studies, 29(2), 99-120.