Shading design has been a frequently discussed topic in both practice and the academia. This presentation will demonstrate a user-friendly method for shading design which links daylight simulation based on Radiance and multi-objective genetic algorithms, thus far used primarily in the computer science field of artificial intelligence and computer-automated design. Multiple objectives such as daylight availability and glare control can be set based on lighting requirements of specific function of the space, to provide large range of shading application. The resulting data can be combined with shading design proposal that provides designers and building owners interested in installing a dynamic shading system with data regarding shading geometry, transmittance, and operation. The multiple objectives include annual Useful Daylight Illuminance (UDI) and annual Daylight Glare Probability (DGP). The optimized parameters of shading can be provided in the early stage of building design to achieve a better performance on indoor daylight environment as well as energy saving.
