Multi-Criteria Optimization of Roof Systems in Airport Warehouses through Generative Design and Climate Simulation: A Case Study in Airport Industrial Architecture

Authors

  • Jhordan Renzzo Cabel Aguilera Colegio de Arquitectos del Perú Regional Lima, Av. San Felipe 999, Jesús María, Lima, Perú

DOI:

https://doi.org/10.17268/

Keywords:

Generative Design, Climate Simulation, Parametric Architecture, Industrial Roof Systems, Multi-Objective Optimization

Abstract

This research explores the application of generative design and early-stage climate simulation to optimize industrial roof systems in semi-open warehouses at Jorge Chávez International Airport. Three design solutions are compared: the client’s original scheme, an architectural proposal developed during professional practice, and an alternative generated through multi-objective optimization algorithms supported by machine learning. Using tools such as Ladybug Tools and Wallacei X, environmental performance was assessed based on EPW data, with emphasis on shading coverage, UTCI, and MRT. The results indicate that, although the client-delivered solution complies with the evaluated parameters, the generative design alternative enhances the technical performance of the original proposal by achieving a more optimized geometry under multiple optimization criteria. The study highlights the potential of computational design in the early stages of industrial projects, improving passive performance under real technical and operational constraints.

 

References

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Published

2026-10-03

Issue

Section

Artículos Originales

How to Cite

Multi-Criteria Optimization of Roof Systems in Airport Warehouses through Generative Design and Climate Simulation: A Case Study in Airport Industrial Architecture. (2026). SCIÉNDO INGENIUM, 22(3), 13-32. https://doi.org/10.17268/