Constraint handling methods for a generative envelope design using genetic algorithms: The case of a highly constrained problem - Archive ouverte HAL
Article Dans Une Revue International Journal of Architectural Computing Année : 2022

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

Résumé

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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Dates et versions

hal-04742017 , version 1 (17-10-2024)

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Claire Duclos-Prévet, François Guéna, Mariano Efron. Constraint handling methods for a generative envelope design using genetic algorithms: The case of a highly constrained problem. International Journal of Architectural Computing, 2022, 20 (3), pp.587-609. ⟨10.1177/14780771221120577⟩. ⟨hal-04742017⟩

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