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

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id caadria2020_035
authors Pereira, Inês, Belém, Catarina and Leitão, António
year 2020
title Escaping Evolution - A Study on Multi-Objective Optimization
source D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 295-304
summary The architectural field is currently experiencing a paradigm shift towards a more environmentally-aware design process. In this new paradigm, known as Performance-Based Design (PBD), building performance emerges as a guiding principle. Unfortunately, PBD entails several problems, for instance, building design is often associated with the simultaneous assessment of multiple performance criteria, which dramatically increases the complexity of the problem. In this vein, recent works claim that coupling optimization tools with PBD approaches allows for more efficient and optima-oriented strategies. This approach, known as Algorithmic Optimization, is based on the use of an optimization tool combined with a parametric model of a design to iteratively generate more efficient design alternatives. This paper focus on evaluating and comparing different classes of Multi-Objective Optimization (MOO) algorithms, namely, metaheuristics and model-based ones. In addition, in order to try to better understand the algorithms' suitability to different optimization problems, this research analyses two different MOO design problems.
keywords Performance-Based Design; Algorithmic Optimization; Multi-Objective Optimization
series CAADRIA
email ines.pereira@tecnico.ulisboa.pt
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100%; open Wortmann, T (2017) Find in CUMINCAD Opossum: Introducing and Evaluating a Model-based Optimization Tool for Grasshopper , Proceedings of the CAADRIA Conference, pp. 283-292

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