Aviation Route Optimization

Abstract

The aviation sector contributes approximately 2–3% of global carbon dioxide emissions, with fuel consumption representing a major operational cost for airlines. As the demand for air travel continues to rise, optimizing flight routes presents a critical opportunity to reduce fuel usage, cut emissions, and improve overall efficiency. This review presents a comprehensive analysis of current strategies and emerging technologies in aviation route optimization, including wind-aware trajectory planning, machine learning algorithms, network-level airspace decongestion, and integration with sustainable aviation fuels (SAF). A wide range of studies demonstrate that wind-optimal routing can yield 1–4% fuel savings on long-haul flights, while artificial intelligence (AI)-based planning methods report reductions up to 14%. Meanwhile, SAF adoption shows strong compatibility with existing propulsion systems and contributes to lifecycle emission reductions. This review also examines hybrid-electric aircraft models and predictive energy management systems as complementary developments in energy optimization. Key findings indicate that combining route optimization with fuel innovation can substantially lower the environmental impact of aviation without requiring major infrastructure changes. The paper concludes with recommendations for integrated optimization approaches and identifies future research opportunities, including real-time decision support systems, SAF scaling, and regulatory incentives. This work provides valuable insights for researchers, engineers, policymakers, and airline operators working to enhance the energy efficiency and sustainability of aviation.