Design and optimization of form and facade of an office building using the genetic algorithm

One of the most important sustainable building design goals is energy performance throughout the life cycle of the building. In this article, the optimization of an office building facade has been performed using a genetic algorithm with the sustainability approach. Multi-objective optimization using an The Strength Pareto Evolutionary Algorithm (SPEA-2) algorithm gives the amount of solar radiation received by the building's envelope and useful interior space and shape coefficient of the design based on the cooling load, heating load, and natural light supplied to the building. In order to achieve the project objectives, parametric modeling was used with Grasshopper software and environmental analysis tools, Ladybug and Honeybee. In both optimization steps, the optimal solution was selected on the Pareto front and, according to the designer, the decision was made between the optimal results. Optimization has led to an improvement in usable space, reduced thermal load, and improved natural light in the building. Using Pareto front, genetic algorithms and parametric modeling have a significant role in developing a sustainable design. The process and results of this research help architects and designers to find a more sustainable design and facade for the building.