This article compares the performance of an adaptive single-objective fa & ccedil;ade system with that of a multiobjective optimized fa & ccedil;ade, focusing on energy generation and visual comfort in office buildings in semi-arid climates. A kinetic dual-axis PV module was combined with parametric modeling and environmental simulation tools (Rhino/Grasshopper, Honeybee, Radiance, Daysim). It was tested through multi-objective optimization using a genetic algorithm (Octopus). The system was applied to a south-facing office room in Tehran, Iran, and was analyzed during critical seasonal hours. The multi-objective optimized fa & ccedil;ade achieves Useful Daylight Illuminance (UDI) between 300 and 3000 lx in more than 75% of the task area during the selected occupied hours. It provides superior hUDI compared to the adaptive single-objective fa & ccedil;ade. The multi-objective optimized system maintained a Daylight Glare Probability (DGP) below 0.35 for all selected critical hours, ensuring visual comfort. Both adaptive single-objective and multi-objective fa & ccedil;ades demonstrated the potential to reduce energy use by 33.95% and 33.42%, respectively, when compared to an unshaded window, while also enhancing visual comfort. However, implementing an adaptive solar tracking system alone led to potential glare or underlit conditions at certain times, highlighting the trade-off between energy gain and visual comfort. The results of this study indicate that dynamic PV fa & ccedil;ades can simultaneously enhance energy performance and occupant comfort when optimized by multi-objective optimization frameworks. This research contributes to the development of responsive building envelopes suited for solar-intensive regions.