Abstract With the continuous development of aviation technology, the design of airborne system architectures has become increasingly complex and requires trade-offs among multiple objectives. Traditional design methods often fail to optimize multiple objectives simultaneously, leading to limitations in system performance. To address this issue, this paper proposes an AI-assisted multi-objective trade-off method for airborne system architecture, which aims to achieve efficient optimization and trade-off of multiple objectives through AI technology. Combined with a dynamic constraint handling mechanism, this method addresses the pain points of low search efficiency in high-dimensional design spaces and difficulty in balancing multi-objective conflicts in traditional methods.
Ye et al. (Tue,) studied this question.