Interactive Multi-Objective Optimization for Military Helicopter Route Planning

Information overload and the labor-intensive nature of the military decision-making process have made human decision-making deficient in modern warfare. To mitigate the current deficiencies, AI systems have been proposed. In a military context, these systems should be reliable and explainable, warranting a human-AI collaboration approach. One process that can greatly benefit from decision support is military helicopter route planning. It has many different conflicting criteria related to it, necessitating multi-objective optimization (MOO) techniques. In the literature, there is a lack of research on the decision-maker’s role. To fill this gap, interactive MOO is proposed to utilize the advantages of human-AI collaboration and create a shared understanding of the problem and its tradeoffs. Unlike the current interactive MOO research, the project is done with the active involvement of domain experts. Four different studies are proposed to investigate this problem. First, a literature study will be performed to review the state of the art. Next, an interactive MOO method will be designed, which will be applied to an Air Interdiction mission. Simultaneously, we will investigate the effect of the level of detail of threat modeling on the resulting optimization problem. Finally, the decision-support tool will be applied to a Strike Coordination and Reconnaissance mission.