This paper extends the applicability of generative design for space planning frameworks for ongoing and guided post-occupancy modifications. It involves the comparison of a graph-based productive-congestion simulation with empirical data and the use of a metaheuristic search algorithm to calibrate and fine-tune simulation parameters for greater accuracy. This methodology is demonstrated through a real-world generative designed case-study and the post- occupancy collection and processing of movement data through custom com- puter vision workflows
CITATION STYLE
Villaggi, L., Stoddart, J., Zhang, P., Tessier, A., & Benjamin, D. (2020). Design Loop: Calibration of a Simulation of Productive Congestion Through Real-World Data for Generative Design Frameworks. In Impact: Design With All Senses (pp. 376–389). Springer International Publishing. https://doi.org/10.1007/978-3-030-29829-6_30
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