研究人员利用Scikit-decide框架结合OpenAP飞机性能模型和NOAA风数据开发了航班路径优化方案，通过计算最优飞行轨迹来降低燃油成本1。该框架经过6年开发周期，集成了强化学习、自动规划和调度等多项功能1。
具体应用中，波音787-9从纽瓦克飞往罗马的8.5小时航程燃油成本约68,000美元1。在欧洲航线的对比测试显示，从图卢兹至柏林的优化航线耗时7666秒、燃油消耗5855千克1；而图卢兹至华沙的路线虽然距离增加500公里，但通过优化可减少45分钟飞行时间，燃油消耗降至5600千克1。阿姆斯特丹至法兰克福航线上，空客A320的燃油消耗为1625.6千克，波音737为1622.1千克1。
该优化系统的飞机数据库包含17架波音、13架空客和5架巴西航空工业公司飞机1。发动机库覆盖427台引擎，涵盖通用电气（108台）、CFM国际（94台）、普惠（85台）和劳斯莱斯（62台）等主要制造商1。
A technical approach combining the Scikit-decide framework with aircraft performance modeling and wind data is being used to calculate fuel-efficient flight routes across Europe.1 The Scikit-decide framework, developed over a six-year period, integrates reinforcement learning, automated planning, and scheduling capabilities to support route optimization.1
Demonstrations of the system reveal significant variations in fuel efficiency across different routes and aircraft types. A flight from Toulouse to Berlin requires 7,666 seconds of flight time and consumes 5,855 kilograms of fuel, while the longer Toulouse-to-Warsaw route covers an additional 500 kilometers yet completes in 6,154 seconds and burns only 5,600 kilograms of fuel—approximately 45 minutes faster.1 On the Amsterdam-to-Frankfurt corridor, an Airbus A320 consumes 1,625.6 kilograms of fuel compared to 1,622.1 kilograms for a Boeing 737.1 For longer-haul operations, a Boeing 787-9 flying from Newark to Rome over 8.5 hours incurs approximately $68,000 in fuel costs.1
The OpenAP database underlying these calculations encompasses 35 aircraft models, including 17 Boeing variants, 13 Airbus models, and five aircraft from Embraer.1 The associated engine database contains 427 powerplants from leading manufacturers: General Electric operates 108 engines in the database, CFM International 94, Pratt & Whitney 85, and Rolls-Royce 62.1
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