الفهرس 
Optimizing parametric light shelf system performance in deep office spaces
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Abstract
Literature in the fields of numerical modeling and deep spaces light systems were reviewed. A reliable numerical model 2Rhino Grass Hopper3 was selected to perform a parametric study to select the adequate parameters to simulate deep office spaces to reach a reliable light system to them. Different parameters were tested and the most applicable of which were selected. This process was achieved several times until convergence was attained. A virtual deep space was set with certain dimensions and was investigated as case study. Results were obtained and analyzed from which guidelines were designated to design a light system with a reliable performance. Innovative about this study is the procedure of selecting the reliable parameters with a complicated numerical modeling technique, where 6552 and 427 runs were achieved. This technique is Parametric Genetic Algorithm, where it is inspired by natural selection to generate high-quality optimization