Research Information System
Thesis Type: Postgraduate
Institution Of The Thesis: Gazi Üniversitesi, Fen Bilimleri Enstitüsü, Turkey
Approval Date: 2019
Thesis Language: Turkish
Student: ŞULE BETÜL DEMİRKOL
Supervisor: ARZU ÖZEN YAVUZ
Abstract:The architectural design process is quite complex. In the early stages of the design, many decisions that affect each other must be made and many variables must be considered. Therefore, it is important to make the right decisions. However, it is still very difficult to predict all the possible consequences of the decisions made and to reach the optimum result. Therefore, especially with the development of computational design approaches, many methods and technical tools have been used to assist architectural design. One of these methods is the Genetic Algorithm approach, which is based on Darwin's theory of evolution and the logic of proliferation in living things. Genetic Algorithm is a productive search algorithm that simulates the growth and development processes in living things and thus achieve the desired optimum result via scanning a large solution space rapidly. It is also useful for problems that need to be optimized at the same time as many variables, such as real-life problems thanks to parallel search. In this study, a productive genetic algorithm model is inspired by sudoku solution logic, which can help the designer to produce architectural forms, has been created. This model based on the analysis and production rules of Sudoku puzzles is named the SuGe model.