Multi-Objective Evolutionary Sunshade Design

Toma, Farzana Haque and Nitschke, Geoff (2025) Multi-Objective Evolutionary Sunshade Design, Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2025), Málaga, Spain.

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Abstract

Sunshades integrated into building facade design critically influence the building’s thermal conditions, natural lighting, energy usage, and occupant comfort. However, heuristic designs often neglect the multi-faceted trade-offs among these objectives. This study compares two multi-objective evolutionary algorithms, NSGA-II and MO-CMA-ES, in optimizing five performance metrics: thermal comfort, Useful Daylight Illuminance (UDI), energy consumption, outside view obstruction, and cost.We integrate annual energy and daylight simulations, incorporating real-world weather data from Cape Town, South Africa, and Nairobi, Kenya. Results indicate that both MO-EAs generate Pareto-optimal sunshades exceeding the performance of five traditional designs for all metrics. In cooler climates, the best solutions featured upward-angled fins to admit beneficial solar gain, while warmer climates favored configurations blocking high-angle sunlight. These findings underscore the importance of climate-specific optimization for identifying costeffective, occupant-friendly building designs to balance daylight management and energy efficiency.

Item Type:	Conference paper
Subjects:	Computing methodologies > Artificial intelligence
Date Deposited:	13 Oct 2025 12:27
Last Modified:	13 Oct 2025 12:27
URI:	https://pubs.cs.uct.ac.za/id/eprint/1745

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