| Title |
The Multi-objective Optimization Using Evolutionary Algorithm to Design Architectural Layouts |
| Authors |
장동국(Chang, DongKuk) ; 박주희(Park, Joohee) |
| DOI |
https://doi.org/10.5659/JAIK.2022.38.11.37 |
| Keywords |
Architectural layout; genetic algorithm; multi objective optimization |
| Abstract |
This research aims to propose an efficient genetic algorithm model that generates a high-quality set of alternatives in architectural design
where various objectives interact and compete. By integrating a novel location-based genotyping expression approach into an architectural
design domain, an automated model would generate architectural layout forms using a genetic algorithm. Depending on the degree of fitness
to the architectural layout form, the initialization and crossover method based on adjacent nodes proposed in this study exhibited different
morphological characteristics. However, both quickly accomplished the desired result. The evolutionary algorithm and the fitness function for
evaluating architectural layouts provided the opportunity to rapidly produce the best alternatives out of a large pool of options by evaluating
user requirements and properties as used during the preliminary stages of architectural design. In a generating environment where many
degrees of fitness are applied simultaneously and that contribute to fitness, the Pareto optimal method was utilized to provide balanced
alternatives between multiple user requirements. |