id 
ecaade2018_323 
authors 
Newton, David 
year 
2018 
title 
MultiObjective Qualitative Optimization (MOQO) in Architectural Design 
source 
KepczynskaWalczak, A, Bialkowski, S (eds.), Computing for a better tomorrow  Proceedings of the 36th eCAADe Conference  Volume 1, Lodz University of Technology, Lodz, Poland, 1921 September 2018, pp. 187196 
summary 
Architectural design problems are often multiobjective in nature, involving both qualitative and quantitative objectives. Previous research has focused exclusively on the development of multiobjective optimization algorithms that work with multiple quantitative objectives. No previous research has looked at the topic of multiobjective qualitative optimization (MOQO), in which multiple qualitative objectives are optimized simultaneously. This research addresses MOQO through the development of a unique multiobjective optimization algorithm for the conceptual design phase that uses threedimensional convolutional neural networks (3D CNNs) to measure userdefined qualities in architectural massing models. 
keywords 
multiobjective optimization; generative design; multiobjective qualitative optimization; algorithmic design 
series 
eCAADe 
email 
david.newton@unl.edu 
full text 
file.pdf (10,625,919 bytes) 
references 
Contenttype: text/plain

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last changed 
2018/07/24 10:22 
