CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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id caadria2024_21
authors Arisman, Arman, Widiastuti, Indah, Indraprastha, Aswin and Sudradjat, Iwan
year 2024
title Architects' Responses to Practicing Generative Design for Form Finding in the Schematic Design Stage
source Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 3, pp. 29–38
doi https://doi.org/10.52842/conf.caadria.2024.3.029
summary Generative design's future impact on architectural processes relies on its successful integration into the established workflow of architects, as prior experiences indicate that technological innovations struggle when not aligned with existing work cultures. This study examines how architects respond to the challenge of practicing generative design, using the genetic algorithm technique, and focusing on the form-finding process, to achieve optimal design outcomes. The researcher set up an experimental research design involving eight professional architects, whose task is to develop an architectural schematic design based on a given set of algorithms. The interaction between architects and computers as supporting tools during the design process is documented to measure the priority level of given algorithms and time budgeting for every design step. Cognitive reflections of architects are recorded during the experiment, followed by interviews to gather additional insights into their experiences in generative design processes. The findings of this research will provide some insights into the advantages and disadvantages of generative design as an alternative approach to architectural design and the best way to integrate generative design seamlessly into prevailing architects' work culture.
keywords Architectural Design, Conceptual Design, Form Finding, Generative Design, Genetic Algorithm, Protocol Analysis
series CAADRIA
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full text file.pdf (1,226,996 bytes)
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