Algorithm optimization of architectural form through sequential landscape evaluation

Designing architectural and urban spaces based on continuous human spatial experience throughout a sequence may lead to architectural and urban forms not bound to conventional concepts. These forms would be made possible through the combination of a quantitative sequential landscape evaluation and morphological optimization utilizing algorithmic processes. In this study, we introduce a method for evaluating sequential landscapes, in which the configuration of buildings, trees, etc., in view changes as pedestrians move along a particular path, using a genetic algorithm optimization of architectural forms to bring them closer to the designer’s ideals. The method’s validity was tested using two case studies, assuming the design of a sequential landscape in an actual city and park. The results present a more efficient, objective, and reproducible method for designing sequences in buildings, cities, and landscapes, compared to traditional methods.