Evolutionary algorithms for generating urban morphology:
Variations and multiple objectives.
Mohammed Makki, Milad Showkatbakhsh , Aiman
Tabony and Michael Weinstock
International Journal of Architectural Computing, 2018
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.
Architecture, computation, evolution, biology, urban, variation, morphology, genetic algorithm, computer aided design
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