Abstract
Parametric multi-objective optimization tools bear the potential to integrate, optimize, and explore design spaces to support interdisciplinary decision-making. A parametric optimization and decision support tool was developed (POD tool), and an evolutionary multi-objective optimization algorithm implemented (POD MOO tool) to automate design search for flexible integrated industrial building design. Both tools were tested and compared within a user study, simulating an interdisciplinary industrial building design process to evaluate if the MOO creates advanced building options in design search. Evaluations of questionnaires show the preference to search for a design by manipulating parameters instead of automatically generated designs from the algorithm.
Reference
Zahlbruckner, M. A., Reisinger, J., Wang-Sukalia, X., Kan, P., Knoll, M., Kovacic, I., & Kaufmann, H. (2022). Evaluation of parametric multi-objective optimization and decision support tool for flexible industrial building design. In L. C. Tagliabue, A. Chassiakos, D. M. Hall, D. Nikolic, & R. Soman (Eds.), Proceedings of the 2022 European Conference on Computing in Construction (pp. 115–122). https://doi.org/10.35490/EC3.2022.202
