A Customer-Oriented Holistic Approach to Solar Shading Design: Enhancing Efficiency in an Existing Educational Building

Shading system design is a complex, multi-objective optimization problem that requires balancing interdependent economic, environmental, social, energy, architectural, and daylighting factors, while also integrating decision-makers’ preferences and user satisfaction. This study aims to develop and validate a hybrid decision-support framework that addresses both quantitative and qualitative data under uncertainty to improve shading system performance. This paper proposes a novel framework that integrates fuzzy logic with multi-criteria decision-making (MCDM) methods. The Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) is employed for criteria prioritization, whereas the Fuzzy Quality Function Deployment (Fuzzy-QFD) translates customer needs into technical requirements. Two evolutionary algorithms, the Single-Objective Genetic Algorithm (SOGA) and the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), were implemented and compared. The framework was validated through its application to an existing educational building in Mansoura, Egypt, evaluating both fixed and dynamic shading solutions. The results indicate that the proposed framework effectively translates customer requirements into design criteria and accurately identifies optimal shading solutions, with SOGA outperforming NSGA-II in optimization performance, while dynamic shading systems significantly enhance glare control and visual comfort, thereby confirming the framework’s efficiency in managing interdependent objectives under uncertain conditions. Overall, the framework provides a robust and systematic methodology for incorporating customer satisfaction into shading design and advancing sustainable building performance.