Next-generation air routing
Integrating AI, multi-objective optimization, and collaborative decision making for efficient and sustainable flight planning
DOI:
https://doi.org/10.35335/emod.v16i3.66Keywords:
Artificial intelligence (AI), Collaborative decision making, Efficient and sustainable flight planning, Multi-objective optimization, Next-generation air routingAbstract
Next-generation air routing aims to revolutionize flight planning by integrating artificial intelligence (AI), multi-objective optimization, and collaborative decision making to improve efficiency and sustainability. This research investigates the application of these techniques to optimize flight routes, minimize fuel consumption, reduce flight time, and enhance overall operational efficiency. The research develops a mathematical formulation model based on binary decision variables for aircraft routing, considering constraints such as airspace capacity, departure time, time windows, and route connectivity. The formulated model is solved using optimization algorithms to obtain optimized routing decisions. The results demonstrate the potential benefits of next-generation air routing, including reduced fuel consumption, improved flight time, efficient airspace capacity utilization, and logical route connectivity. The research contributes to the ongoing efforts in the aviation industry to address challenges related to efficiency, sustainability, and capacity management in flight planning. The findings provide insights for industry practitioners and policymakers to develop advanced systems and decision support tools for more efficient and sustainable flight operations
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Copyright (c) 2022 Dominković Rosenow, Tsao Tao Lee, Zhu Xue Li
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