Backcasting and a New Way of Command in Computational Design

König, Reinhard; Schmitt, Gerhard

doi:10.3311/caadence.1692

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…This approach has been used at different scales and for different performance objectives. Some researchers focused on urban planning 15,16 and blocks generation. 17 Others studied building morphology 18,19 either focusing on the whole façade or on one element.…”

Section: Literature Reviewmentioning

confidence: 99%

Constraint handling methods for a generative envelope design using genetic algorithms: The case of a highly constrained problem

Duclos-Prévet

Guéna

Efron

2022

International Journal of Architectural Computing

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The use of genetic algorithms as generative and performance design techniques often involves, in practice, constraint handling, which can be a complex task. Moreover, environmental simulations are computationally expensive and managing constraints can avoid wasting time on infeasible solutions. Despite these two incentives, and the benefits of an immense literature, both applied and theorical, on constrained optimization, there are only few guidelines and tools directly applicable by architects to address this issue. This paper proposes to fill this gap by identifying, classifying, and implementing different constraint management techniques available to architects. Seven methods have been tested for a highly constrained envelope design problem, consisting in the optimization of a sun-shading system. Three of them are easily replicable to different types of projects while the four others need to find a problem-specific heuristic. It appears that the second category is more efficient but implies the use of generative techniques that are more difficult to implement than parametric models.

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Section: Literature Reviewmentioning

confidence: 99%

Constraint handling methods for a generative envelope design using genetic algorithms: The case of a highly constrained problem

Duclos-Prévet

Guéna

Efron

2022

International Journal of Architectural Computing

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Interactive Urban Synthesis

König

Miao²,

Knecht

et al. 2017

Communications in Computer and Information Science

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Computational Optimisation of Urban Design Models: A Systematic Literature Review

Tay,

Ortner,

Wortmann

et al. 2024

Urban Science

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The densification of urban spaces globally has contributed to a need for design tools supporting the planning of more sustainable, efficient, and liveable cities. Urban Design Optimisation (UDO) responds to this challenge by providing a means to explore many design solutions for a district, evaluate multiple objectives, and make informed selections from many Pareto-efficient solutions. UDO distinguishes itself from other forms of design optimisation by addressing the challenges of incorporating a wide range of planning goals, managing the complex interactions among various urban datasets, and considering the social–technical aspects of urban planning involving multiple stakeholders. Previous reviews focusing on specific topics within UDO do not sufficiently address these challenges. This PRISMA systematic literature review provides an overview of research on topics related to UDO from 2012 to 2022, with articles analysed across seven descriptive categories. This paper presents a discussion on the state-of-the-art and identified gaps present in each of the seven categories. Finally, this paper argues that additional research to improve the socio-technical understanding and usability of UDO would require: (i) methods of optimisation across multiple models, (ii) interfaces that address a multiplicity of stakeholders, (iii) exploration of frameworks for scenario building and backcasting, and (iv) advancing AI applications for UDO, including generalizable surrogates and user preference learning.

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Backcasting and a New Way of Command in Computational Design

Cited by 3 publications

References 9 publications

Constraint handling methods for a generative envelope design using genetic algorithms: The case of a highly constrained problem

Constraint handling methods for a generative envelope design using genetic algorithms: The case of a highly constrained problem

Interactive Urban Synthesis

Computational Optimisation of Urban Design Models: A Systematic Literature Review

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