A many-objective optimization approach to design office building façade considering energy-daylight balance concept within prevalent climate types of Iran

The concept of energy-daylight balance in architectural design aims to maximize daylighting while reducing energy consumption. Many parameters influence this concept, although they are not necessarily of equal importance in different climates. This study aims to identify the appropriate weight distribution sets (WDSs) for the most influential parameters of the energy-daylight balance concept, namely energy efficiency, daylighting, visual comfort, and thermal comfort, under the prevalent climate types of Iran. To this end, a many-objective optimization algorithm (NSGA-III) is applied to a parametric design procedure involving design variables related to the window system and a proposed shading system, leading to the identification of the most optimal façade designs for office buildings in each climate. Next, a weighted sum method (WSM) evaluates the Pareto-optimal solutions of each climate type based on nine different WDSs. Analyzing the absolute Pareto-optimal solutions, which are the solutions with the highest WSM scores within each WDS in each climate, reveals that, depending on the climate, prioritizing daylighting, thermal comfort, or energy efficiency objectives leads to the highest overall performances within these solutions. Furthermore, the Friedman test results show that in the design of office buildings in Bandar Abbas, Isfahan, Rasht, or Tehran, the most optimal trade-off between the objectives generally occurs by prioritizing energy efficiency, whereas in Dezful, it is generally achieved by prioritizing daylighting. However, pairwise comparisons of the WDSs reveal that in each climate, there are a number of pairs of sets that are not significantly different. •The concept of energy-daylight balance is studied under different climate types.•Energy, daylighting, thermal, and visual comfort are evaluated simultaneously.•Within each climate, nine different weight distribution sets are considered.•Absolute Pareto-optimal solutions perform differently within each climate.•Under different climates, weight distribution sets do not differ significantly.