Collaborative strategic conflict management for 4D trajectories under weather forecast uncertainty

The design of decision support tools for strategic conflict management (SCM) needs to integrate and manage uncertainty while accommodating the diverse performance preferences of multiple stakeholders. This paper proposes a novel collaborative SCM approach for four-dimensional (4D) trajectories under weather forecast uncertainty, integrating trajectory prediction, strategic conflict detection and resolution, and collaborative decision-making. A 4D grid-based conflict risk assessment method is introduced for trajectories generated by the ensemble trajectory predictor, incorporating weather uncertainty from ensemble forecasts. A multi-objective optimization model is formulated to reorganize aircraft trajectories within free route airspace, employing rerouting, flight level allocation, and speed control to optimize safety, efficiency, and predictability. Predictability is explicitly considered to enhance adherence to planned trajectories and reduce operational uncertainty, while equity is incorporated as a constraint to ensure a fair distribution of trajectory adjustments. To efficiently solve this large-scale multi-objective SCM problem, a decomposition-based memetic algorithm (DMA) is proposed. The DMA combines a decomposition-based global search framework with local refinement via a hybridization strategy to achieve a good balance between exploration and exploitation. The effectiveness of the proposed method is validated using a simulation scenario featuring 760 flights in the high-density western China airspace. Results demonstrate that the approach effectively identifies trade-offs between different stakeholder objectives and provides optimized solutions that support collaborative decision-making in strategic conflict management.