Multi-objective optimization method of airborne system architecture assisted by an intelligent algorithm

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.