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http://dx.doi.org/10.5659/JAIK.2022.38.11.37

The Multi-objective Optimization Using Evolutionary Algorithm to Design Architectural Layouts  

Chang, DongKuk (School of Architecture, Chosun University)
Park, Joohee (School of Architecture, Chosun University)
Publication Information
Journal of the Architectural Institute of Korea / v.38, no.11, 2022 , pp. 37-48 More about this Journal
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.
Keywords
Architectural layout; genetic algorithm; multi objective optimization;
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Times Cited By KSCI : 2  (Citation Analysis)
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