Abstract
In this paper, a multiple optimization system using genetic algorithms is proposed. Using this system, plural objectives with mutually differing evaluation criteria can co-evolve and co-exist according to given overall conditions. Three case study simulations are performed in which three architectural spaces are formed using a cellular automata model and the L-system within a building site under the following conditions: internal conditions— stability, density, aspect ratio, and natural lighting; and external conditions— building coverage and floor area ratio. For these case studies, results showed that these three architectural spaces can co-evolve and co-exist autonomously, adapting to external site conditions using the proposed multiple optimization system.
