No abstract

The aeronautical industry requires important quantities of fossil fuel to sustain flights. Fuel burn releases pollution particles to the atmosphere such as carbon dioxide. The aeronautical industry has set itself the goal of diminishing CO 2 emissions for the forthcoming years. A way of reducing fuel consumption is by improving en-route operations. For long haul flights, cruise is the flight stage that requires the most fuel consumption. Taking advantage of tailwinds reduces the flight time, thus reducing the fuel requirements. In this paper, an algorithm based on the Ant Colony Optimization was developed to optimize the lateral navigation reference trajectory of a commercial aircraft. Following a constant flight level, the algorithm was able to identify favorable wind areas, and to lead the aircraft to take advantage of these winds to optimize the flight cost. The aircraft model was a numerical performance model constructed from experimental flight data, where weather information was obtained by using information from Weather Canada. Results showed important fuel savings for different long haul flights. NomenclatureCDA = Continuous Descent Approach CDG = Paris Charles De Gaulle International airport (France) CI = Cost Index LNAV = Lateral Navigation NRT = Tokyo Narita International Airport (Japan) Pherom i = Pheromone level at a given path. PDB = Performance Database P i = Waypoint Selection Probability PTP = International Airport of Point à Pitre (Guadeloupe) TOC = Top of climb TOD = Top of decent VNAV = Vertical Navigation WA = Wind Azimuth WS = Wind Speed YUL = Montreal Pierre Eliot Trudeau International Airport (Canada) γ = Pheromone evaporation rate