(untitled) (Future Cities and Environment, 2024)
The architectural design process is complex, involving diverse objectives that may be contradictory, and on which orientation exerts significant influence. The artificial intelligence application, Generative Design facilitates solving multi-objective design dilemmas through the creation and evaluation of numerous design alternatives. However, its exploration in educational buildings in hot arid climates remains limited. Given the impact of spaces’ function distribution, this study aims to optimize it in the typical plans of educational buildings. Employing a multi-objective design approach to enhance environmental performance. The study is conducted and evaluated in national universities in Egypt as a case study, specifically in Assiut City. The results revealed that the optimum design for a certain objective has not equated to optimal performance for other goals, highlighting an inherent contradiction between them. Among 26,334 possible alternatives for spaces’ function distribution, the difference between the optimal scenario and the least favourable one is significant for the parameters related to study spaces: natural daylighting, and visual comfort, ranging from 10% to 24%, besides around 1% difference for parameters related to the whole building, including energy consumption, thermal comfort, and carbon emission. This research offers a framework applicable to various building types. Additionally, it encourages decision-makers to adopt a no-cost sustainable design approach.