Multi-dimensions optimization for optimum modifications of light-shelves parameters for daylighting and energy efficiency

The greatest role in the building design is to optimize the use of natural daylight harvests to ensure human comfort and energy usage. This research aims to introduce an optimized office workspace that meets both daylight availability and energy efficiency. Honeybee and Ladybug plugins for grasshopper parametric software is utilized to simulate daylight and energy where multi-objective genetic optimization using non-dominated sorting genetic algorithms method is explored with octopus plugin, which is able to provide the best overall solution as a trade-off for multiple and conflicting design objectives simultaneously. The optimization focused on single-objective which shows major differences between daylight availability and energy efficiency while optimization for multi-objective together proved to be an efficient tool to research the trade-offs between the two contradictory objectives. The final best optimum balanced solutions can improve the sDA(300/50%) by decreasing with an average of -11.88%, -2.34%, -5.94%, and -20.78%, while the UDI300-2000 lx increased with an average by 39.39%, 29.23%, 46.17%, and 19.40%. The energy efficiency is slightly increased by + 1.33%, -0.61%, + 1.33%, and + 1.29%, in March, June, September, and December, respectively, compared to the reference model.