Evolutionary algorithms for generating urban morphology: Variations and multiple objectives

Morphological variation of urban tissues, which evolve through the optimisation of multiple conflicting objectives, benefit significantly from the application of robust metaheuristic search processes that utilise search and optimisation mechanisms for design problems that have no clear single optima...

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Bibliographic Details
Published inInternational journal of architectural computing Vol. 17; no. 1; pp. 5 - 35
Main Authors Makki, Mohammed, Showkatbakhsh, Milad, Tabony, Aiman, Weinstock, Michael
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.03.2019
Subjects
genetic algorithm
biology
Architecture
urban
morphology
evolution
computer aided design
variation
computation
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ISSN1478-0771
2048-3988
DOI10.1177/1478077118777236

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Summary:Morphological variation of urban tissues, which evolve through the optimisation of multiple conflicting objectives, benefit significantly from the application of robust metaheuristic search processes that utilise search and optimisation mechanisms for design problems that have no clear single optimal solution, as well as a solution search space that is too large for a ‘brute-force’ manual approach. As such, and within the context of the experiments presented within this article, the rapidly changing environmental, climatic and demographic global conditions necessitates the utilisation of stochastic search processes for generating design solutions that optimise for multiple conflicting objectives by means of controlled and directed morphological variation within the urban fabric.
ISSN:1478-0771
2048-3988
DOI:10.1177/1478077118777236