id 
caadria2020_035 
authors 
Pereira, InÃªs, BelÃ©m, Catarina and LeitÃ£o, AntÃ³nio 
year 
2020 
title 
Escaping Evolution  A Study on MultiObjective 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, 56 August 2020, pp. 295304 
summary 
The architectural field is currently experiencing a paradigm shift towards a more environmentallyaware design process. In this new paradigm, known as PerformanceBased 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 optimaoriented 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 MultiObjective Optimization (MOO) algorithms, namely, metaheuristics and modelbased 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 
PerformanceBased Design; Algorithmic Optimization; MultiObjective Optimization 
series 
CAADRIA 
email 
ines.pereira@tecnico.ulisboa.pt 
full text 
file.pdf (3,355,466 bytes) 
references 
Contenttype: text/plain

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last changed 
2020/08/14 18:39 
