Proceedings of the 2022 European Conference on Computing in Construction


Evaluation of parametric multi-objective optimization and decision support tool for flexible industrial building design

Maria Antonia Zahlbruckner, Julia Reisinger, Xi Wang-Sukalia, Peter Kán, Maximilian Knoll, Iva Kovacic, Hannes Kaufmann
Vienna University of Technology, Austria

DOI: 10.35490/EC3.2022.202
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.
Keywords: decision making support, integrated industrial building design, integrated design, multi-objective optimization, parametric design

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