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Optimisation of daylight admission through window is crucial for alleviating glare while maintaining useful daylight levels in order to enhance occupants' health, visual comfort and moderating lighting energy consumption. Amongst various solutions, fixed external shade is an affordable solution for housing spaces that need to be sophisticatedly designed, especially during the period of increasing home spaces as working environments. In the humid subtropical region, daylight control plays an important role in indoor comfort, particularly with areas with a high window to wall ratio (WWR). Due to the insufficient amount of such study on non-office spaces in Australia, shading-related standards are not addressed in Australian building codes.

The chosen methodology for the research is a quantitative data collection and analysis through field measurement and simulation simultaneously. The first step is a multi-objective optimisation of shading elements through a non-dominated sorting genetic algorithm (NSGA-II) on parametric modelling via Rhino3D CAD and simulation engines (DIVA and ClimateStudio). In the second phase, the Pareto front solutions are validated by experimental measurements within a room with a single north-facing window (the most probable for the daytime glare in Sydney) for the seven most common local window configurations.

Through the simulation of ten genes, 1,560 values and 2.4 × 1,019 of search space, this study found an optimum shade for each local common window layout, resulted in +22% in (UDI) and −16% in views with discomfort glare on average. Moreover, an all-purpose polygonal shade showed an average of 4.6% increase in UDI and a 5.83% decrease in the percentage of views with discomfort glare.

The findings are subject to the room dimensions, window dimensions and layouts, and orientation of windows for selected residential buildings in Sydney.

The study contributes to the development of highly accurate fixed external shading systems with rectangular and tapered-form external shapes. A real-time measurement by luminance-metre sensors and HQ cameras located at six eye levels is conducted to corroborate simulation results of the visual comfort.

The Middle East and North Africa (MENA) region is known for its extreme weather conditions during Summer. A major determinant of the sustainability of the design of a building is its fenestrations. The purpose of this paper is to explore the problem of designing and locating windows on building facades such that a number of relevant criteria to the MENA region are optimised, including solar heat gain, privacy, daylighting and cost of installation.

A multi-objective optimisation problem is proposed with the focus on capturing the requirements of residential dwellings in the MENA region. Since the problem contains conflicting objectives that need to be optimised, a lexicographic approach is adopted. In order to display the Pareto curve, a bi-objective analysis based on the ε-constraint method is utilised.

The conflicting nature of the proposed problem is indicated via the Pareto optimal solutions yielded. Depending on the preference of criteria adopted in lexicographic optimisation, the location of the windows on the building façade tends to change. The bi-objective analysis indicates the importance of balancing out the daylight factor against each of privacy, solar heat gain and installation cost criteria. Furthermore, an analysis conducted in three major cities in the MENA region highlights the discrepancy in design alternatives generated depending on the local climatic condition.

This work proposes a novel mathematical optimisation model which focuses on producing a sustainable design and layout for windows on the facades of residential dwellings located in the MENA region. The proposed model provides designers with guidance through an automated support tool that yields optimised window designs and layout to ensure the sustainability of their designed buildings.