Buildings are a critical element of civilization, within which we spend over around 70% of our lifetime, but also one of the main contributors to the greenhouse effect. It is therefore important to ensure their design guarantees good indoor conditions, while minimizing the environmental footprint. Among the different building elements, the facade is one that most influences these two requisites and thus its design requires, in addition to the traditional aesthetic and functional requirements, the integration of performance criteria from early design stages. However, there are still some barriers to this integration, such as the limited flexibility of design tools, the need for multiple analysis and optimization tools, and their high computational cost. Recent computational design approaches, such as Algorithmic Design (AD), have been facilitating the combination of creative processes with the search for better performing and more sustainable design solutions. However, these approaches require programming skills, which most architects do not have. To maximize its potential for architectural design, efforts should be made to reduce the complexity of AD and approximate it to the architects’ design practice. We address this by proposing an AD methodology and algorithmic framework for facade design that encompasses its different stages, from conceptual design to manufacturing, and requirements, such as aesthetics, environmental performance, comfort, and costs, among others, while supporting the variability and diversity typical of architectural design problems. By combining the framework’s ready-to-use algorithms, multiple design scenarios can be considered, and various design requirements addressed, helping to achieve the goals established by both the 2030 Agenda and Industry 4.0.
