Performance-Driven Generative Design for Daylighting Optimization in a Tangerang Aerotropolis Office Building
DOI:
https://doi.org/10.9744/dimensi.53.2.213-229Keywords:
Performance-driven generative design, daylighting, genetic algorithmAbstract
Daylighting in tropical climates may increase glare risk in office buildings. This issue is particularly relevant in the Tangerang Aerotropolis area, where humid tropical conditions and airport operational safety regulations constrain building development. This study optimized daylighting performance in an office building using a Performance-Driven Generative Design approach. The workflow integrated Rhinoceros 3D, Grasshopper, ClimateStudio, and Galapagos to evaluate six envelopes and building mass variables. The optimization evaluated 950 design alternatives across 18 generations using UDI₁₀₀–₃₀₀₀ as the objective function. A maximum UDI₁₀₀–₃₀₀₀ of 95.5% was achieved with a WWR of 0.47, window height of 2.53 m, shading spacing and depth of 0.40 m, building width of 12 m, and orientation of 76°. Best-performing configurations converged within WWR 0.40–0.47, window height 2.50–2.60 m, shading spacing 0.30–0.50 m, shading depth 0.30–0.40 m, building width 12–13 m, and orientation 72°–84°. The results identified a high-performing configuration and recurring parameter ranges among the best-performing solutions.
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