CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

id caadria2013_198
authors Chee Zong Jie and Patrick Janssen
year 2013
title Exploration of Urban Street Patterns – Multi-Criteria Evolutionary Optimisation Using Axial Line Analysis
source Open Systems: Proceedings of the 18th International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2013) / Singapore 15-18 May 2013, pp. 695-704
wos WOS:000351496100068
summary In urban design, researchers have developed techniques to automate both the generation and evaluation of urban street patterns. In most cases, these approaches are investigated in isolation from one another. Recently, a number of researchers have attempted to couple these approaches, in order to enable larger numbers of street patterns to be generated and evaluated in an iterative loop. However, to date, the possibility of fully automating the generative-evaluative loop using optimisation algorithms has not been explored. This research proposes an explorative design method in which urban street patterns can be optimised for multiple conflicting performance criteria. The optimisation process uses evolutionary algorithms to evolve populations of design variants by iteratively applying three key procedures: development, evaluation, and feedback. For development, a generative technique is proposed for constructing street patterns. For evaluation, various performance measures are used, including in particular Space Syntax based Axial Line analysis. For feedback, a Pareto-ranking algorithm is used that ranks street patterns according to multiple criteria. The proposed method is demonstrated using an abstract scenario in which orthogonal street patterns are evolved for a small urban area.  
keywords Axial line analysis, Generative modelling, Evolutionary algorithms, Decision chain encoding, Urban street patterns 
series CAADRIA
email desmonde.chee@yahoo.com
full text file.pdf (2,015,976 bytes)
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