2020
DOI: 10.1177/1478077120951948
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The design of social and cultural orientated urban tissues through evolutionary processes

Abstract: The research examines how social and cultural properties can be utilised as an alternative planning scheme to improve urban morphology and enhance the overall experience of individuals within the city. The aim is for these socio-cultural properties to be translated into quantitative data sets that define the morphological characteristics of the urban tissue. Through the use of evolutionary optimisation methods, the process of urban growth is simulated through a series of individuals that adapt and optimise for… Show more

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Cited by 5 publications
(1 citation statement)
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“…In doing so, access to MOEAs by designers (both for developers as well as users) has been more streamlined than any other point in history, allowing for innovative approaches to responding to, and designing for, design problems comprising multiple conflicting objectives. In urban design, the value of MOEAs is amplified, as it requires a performance-based metric approach to the design problem, allowing designers to integrate climatic, environmental, and urban metrics as key drivers for the algorithm [11][12][13]. This data-driven approach to solving the complexity associated with the urban fabric informs all stages of the algorithmic process; however, key to this is the coupling of the user-driven analysis of the data and the way in which it informs the results outputted by the optimisation run.…”
Section: Introductionmentioning
confidence: 99%
“…In doing so, access to MOEAs by designers (both for developers as well as users) has been more streamlined than any other point in history, allowing for innovative approaches to responding to, and designing for, design problems comprising multiple conflicting objectives. In urban design, the value of MOEAs is amplified, as it requires a performance-based metric approach to the design problem, allowing designers to integrate climatic, environmental, and urban metrics as key drivers for the algorithm [11][12][13]. This data-driven approach to solving the complexity associated with the urban fabric informs all stages of the algorithmic process; however, key to this is the coupling of the user-driven analysis of the data and the way in which it informs the results outputted by the optimisation run.…”
Section: Introductionmentioning
confidence: 99%