Generative Facade Elements Recommendation for Diyarbakır Traditional U Plan Type Residences




generative systems, genetic algorithms, shape grammar, traditional texture


Genetic algorithm (GA) are based on the continuation of fitter ones’ lives considering the natural evolution. Data are coded as genes in the genetic algorithms. Optimal solutions can be achieved through the methods of crossing and mutation performed on these coded genes. Facade elements of the buildings with an architectural design in this study are independent of sustainability-related concerns, suggesting a great issue for the new buildings to be constructed in the traditional pattern. Accordingly, using the genetic algorithm method, proposals were presented for the new door and window typologies with genetic fitness for the architectural designing process of the buildings to be constructed in Suriçi Region, Diyarbakır, Turkey. Shape grammar, fractal and genetic algorithm, three generative designing systems, were used as the methods. Utilizing the genetic algorithm method, a field study was performed for the proposal of new door and window typologies with the fitness value. The field study was assessed through the plans and facade analyses regarding six Diyarbakır traditional houses with U plan type in Suriçi region of Diyarbakır. An identity card was created for the plan and facade data of the buildings and transferred to the table. Then, the door and window typologies of the exterior facade elements of each examined building were crossed within themselves with the GA method. As a result of the crossover, alternative joinery typologies with a total of 31 windows and 53 different door typologies with compatibility values were produced. Thus, the sustainability of the data of traditional joinery typologies for use in contemporary houses has been ensured. In conclusion, optimal alternative typologies were presented in regard to every chopping typology assessed with the genetic algorithm method. It is thought that this study should be a method that can be used in the production of exterior joinery typologies of contemporary houses to be built in many different cities of our country, especially in the historical texture. Thus, by using the GA method for the production of exterior joinery typologies of contemporary houses to be built in the region, different designers will be able to obtain various designs compatible with the traditional architectural texture while preserving their originality.


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Author Biographies

Mizgin Gökçe Salık, Dicle University

Mizgin Gökçe Salık a PhD student   at Dicle University, Faculty of Architecture, Department of Architecture.  she worked in the private sector on application projects and designs. She is currently working as a lecturer    at Department of Architecture and Urbanism in the Ağrı İbrahim Çeçen University. She has publications on architecture.

F. Demet Aykal, Dicle University

F. Demet Aykal is currently working as a professor of planning, planning theory and design approaches at Dicle University, Faculty of Architecture.F. Demet Aykal serves as the vice dean of the faculty of architecture in. She has publications in journals in many fields related to architecture and is a referee.


Aksoy, M. (2001). Varolan Tasarım Dilleri ve Yeni Tasarım Dilleri Bağlamında Biçim Grameri Analizi. Published Doctoral Thesis, İstanbul Technical University, Istanbul.

Akpınar, F. (2009). Yerleştirme Rotalama Problemi İçin Bir Genetik Algoritma. Published Master’s Thesis, Istanbul Technical University, Istanbul.

Braysy, O. (2001). Genetic algorithm for the vehicle routing problem with time windows, Arpakannus, Special Issue on Bioinformatics and Genetic Algorithms, p. 33–38.

Bentley, P. (1999). An Introduction to Evolutionary Design by Computers. Evolutionary Design by Computers, Chap 1.; Kauffman, M. (Editor), London, p. 1-72


Çalışır, K. (2015). Olimpik Havuz Plan Şeması Tasarımında Genetik Algoritmaya Dayalı Bir Model. Published Master’s Thesis, Istanbul Technical University, Istanbul.

Emel G. & Taşkın Ç. (2002). Genetik Algoritmalar ve Uygulama alanları. Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi , Volume XXI, Issue no. 1, p. 129-152

Fischer T. & Herr C. M. (2001). Teaching Generative Design.

Fığlalı A. & Engin O. (2002). Genetik Algoritmalarla Akış Tipi Çizelgelemede Üreme Yöntemi Optimizasyonu, İTÜ Dergisi, p. 1-6.

Goldberg, D. E.(1989). Genetic Algorithms in Search, Optimization and Machine Learning, Alabama: Addison Wesley Publishing Company, p. 7,10,92.

Güngör, Ö. (2010). Genetik Algoritmaya Dayalı Kitlesel Bireyselleştirme Amaçlı Konut Tasarım Modeli. Published Master’s Thesis, Istanbul Technical University, Istanbul.

Holland, J. H. (1975). Adaptation in Natural and Artificial Systems, Ann Arbor: The University of Michigan Press, 2.

Jo, J.H. & Gero, J.S.(1998).Space Layout Planning Using an Evolutionary Approach.

Artificial Intelligence in Engineering ,12:3, p. 149-162.

Karakoyun, M. (2010). Bodrum Geleneksel ve Güncel Konut Mimarisinin Biçim Grameri Yöntemi ile Araştırılması. Published Master’s Thesis, Selçuk University, Konya.

Knight and Stiny (2001). Stiny-2001-a-the-simple-church-cross-plan_fig10_284715627 (Date Accessed: September 18)

Vural, M. (2005). Genetik Algoritma Yöntemi İle Toplu Üretim Planlama. Published Master’s Thesis, Istanbul Technical University, Istanbul.

Yeniay Ö. (2001). An Overview of Genetic Algorithms, Anadolu Üniversitesi Bilim ve Teknoloji Dergisi, 2: 1, p. 37-49.

URL-1 1939-Aerial Photograph

URL-2 1909- View from Suriçi

Knight, T. and Stiny, G. (2001). Classical and non-Classical Computation, arq: Architectural Research Quarterly ,Cambridge Journals, 5, p. 355-372.




How to Cite

Gökçe Salık, M., & Aykal, F. D. (2023). Generative Facade Elements Recommendation for Diyarbakır Traditional U Plan Type Residences. ICONARP International Journal of Architecture and Planning, 11(1), 107–136.