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supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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id acadia17_340
authors Landim, Gabriele; Digiandomenico, Dyego; Amaro, Jean; Pratschke, Anja; Tramontano, Marcelo; Toledo, Claudio
year 2017
title Architectural Optimization and Open Source Development: Nesting and Genetic Algorithms
source ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 340- 349
summary This research presents a general overview of performance-oriented architectural design and how the rise of parametric modeling and algorithm-aided design enable an integrated environment for project design, simulation and optimization. For optimization processes, one of the most used methods in architectural problem solving is genetic algorithms (GAs). However, as the use of GAs becomes more common in the architecture, it is possible to identify a lack of clarity about the methods and procedures operated by the algorithms. Thus, this research seeks to contribute to the field through the implementation of an open source optimization plugin whose method of implemented algorithms, a GA and a nesting algorithm, can be accessed for evaluation, improvement and adaptation to other architectural problems. In the same way, it discusses the relevance of the openness and clarity of the methods employed in optimization processes in architecture. The proposed plugin was tested in an experiment that verified the feasibility of the development of the open source plugin and the efficiency of the method in solving the chosen architectural problem.
keywords algorithm-aided design; optimization; genetic algorithm; nesting; open source; computational / artistic cultures; generative system; simulation & optimization; design methods; information processing
series ACADIA
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