This paper proposes a computational framework that integrates vernacular architecture knowledge (VAK) into genetic algorithms (GA) to enhance architectural design optimization. First, in addition to the parameters required for the design optimization process, constants derived from VAK are introduced. Secondly, an algorithmic model is presented in which these extracted parameters and constants are incorporated into GA processes. The integration of VAK-based constants has the potential to improve architectural design optimization while preserving the local structural characteristics of the design. This approach emphasizes the designer’s expertise by reducing the number of meaningless variations in GA processes and increasing efficiency. The proposed method is demonstrated through a case study that generates design variations for Karaçadır, a traditional structure used by the Yörüks, a nomadic culture in Anatolia. The study incorporates key design elements: cover modules, load-bearings, and connectors to produce variations that preserve the traditional structure of Karaçadır.
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