Optimizing Daylight in Architectural Drawing Rooms Using Political Optimizer: A Case Study of Hot and Dry Regions

This paper introduces a comprehensive framework for optimizing daylight performance in architectural drawing rooms located in hot-arid climates through the integration of building performance simulation and political optimizer algorithms. The study investigates the key challenge of balancing daylight availability with visual comfort in educational spaces characterized by high solar radiation intensities. A sophisticated 3D simulation model was created using MATLAB, embedding 15 CIE standard sky types to accurately represent the dynamic luminous environment of hot-dry regions. Empirical validation conducted in Biskra, Algeria, demonstrated high model accuracy with a mean error of 3.5%. The political optimizer algorithm was employed to solve a multi-objective optimization problem addressing three key performance indicators: illuminance uniformity, Useful Daylight Illuminance (UDI 300–3000 lux), and task-specific illumination levels (300–500 lux). Optimization results indicated marked improvements, with UDI occupancy rates increasing from 20.66% to 37.66%, representing an 82% relative enhancement. The optimal configuration identified includes a 30% window-to-wall ratio, 70% glazing transmittance, and strategic surface reflectances (ceiling: 80%, walls: 65%, floor: 35%). This research provides a validated computational framework that allows architects to make evidence-based design decisions for educational spaces in climatically challenging settings, effectively bridging the gap between building performance simulation and practical architectural applications.