Lateral Reference Trajectory Algorithm Using Ant Colony Optimization

Murrieta-Mendoza, Alejandro; Hamy, Antoine; Botez, Ruxandra Mihaela

doi:10.2514/6.2016-4209

Cited by 6 publications

(3 citation statements)

References 28 publications

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“…Use of a PDB requires a procedure to compute the flight fuel consumption. A complete methodology to compute the flight cost from a database by considering all flight phases such as climb, acceleration, cruise, descent, and deceleration was discussed in [29,30]. In this paper, only the procedure to compute the fuel consumption in the cruise phase is briefly explained.…”

Section: Fuel Burn Model and Trajectory Cost Computationmentioning

confidence: 99%

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Horizontal flight trajectory optimization considering RTA constraints

2020

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The increasing of flights around the world has led to various problems for the aeronautical industry such as saturated air space and higher levels of fossil fuel consumption. The way in which en-route flights are handled should be improved in order to increase airways’ capacity. A solution is to make aircraft to arrive at specific waypoints at a time constraint called Required Time of Arrival (RTA). Fossil fuel brings as a consequence the release of polluting particles to the atmosphere such as carbon dioxide and nitrogen oxides. It is thus desirable to compute the most economical trajectory in terms of fuel burn while fulfilling the RTA constraint. This article proposes a horizontal reference trajectory optimization algorithm based on the Particle Swarm Optimization technique in order to reduce fuel burn while fulfilling the RTA constraint. Results showed that for a flight without RTA constraint, up to 4% of fuel can be saved comparing against the trajectory of reference. The algorithm was normally able to meet the RTA constrain. However, aggressive RTA constraints might reduce the optimization levels of fuel compared with flights without RTA constraint.

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Section: Fuel Burn Model and Trajectory Cost Computationmentioning

confidence: 99%

“…[27]. Dijkstra's Metaheuristic algorithms have been successfully used to compute the optimal LNAV trajectory at fixed altitudes [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Horizontal flight trajectory optimization considering RTA constraints

2020

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“…Metaheuristic algorithms have also been implemented in the trajectory optimization problem such as the artificial bee's colony as in [28] where the most economical vertical reference trajectory with a time constraint was found. The Ant colony optimization was implemented in order to find the most economical lateral reference trajectory taking advantage of winds [29]. The ant colony optimization was also implemented to find the most economical Mach numbers that fulfills a time constraint [30].…”

Section: Introductionmentioning

confidence: 99%

Vertical Reference Flight Trajectory Optimization with the Particle Swarm Optimisation

Murrieta-Mendoza¹,

Ruiz²,

Botez³

2017

Modelling, Identification and Control

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The consumption of fossil fuels in order to power flights leads to undesirable pollution particles to be released to the atmosphere. Fuel also represents an important expense for airlines. For these reasons, it is of interest to reduce fuel burn for a given flight. In this article, the altitudes followed by a commercial aircraft during the cruise phase of a flight, also called vertical reference trajectory, were optimized in terms of fuel burn. The airspace was modelled under the form of a unidirectional graph. Fuel burn was computed using a numerical performance model. The weather forecast was obtained from the model delivered by Environment Canada. The selection of waypoints where to execute the changes in altitudes that provided the most economical flight cost in terms of fuel burn was determined using the particle swarm optimisation (PSO) algorithm. The trajectories provided by the algorithm developed in this paper were compared against simple geodesic trajectories to validate its optimization potential, and against as flown trajectories. Results have showed that up to 6.5% of fuel burn can be saved comparing against simple trajectories, and up to 3.1% was optimized comparing against as flown trajectories.

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Commercial Aircraft Trajectory Optimization to Reduce Flight Costs and Pollution: Metaheuristic Algorithms

Murrieta-Mendoza

Botez

2019

Lecture Notes in Mechanical Engineering

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Lateral Reference Trajectory Algorithm Using Ant Colony Optimization

Cited by 6 publications

References 28 publications

Horizontal flight trajectory optimization considering RTA constraints

Horizontal flight trajectory optimization considering RTA constraints

Vertical Reference Flight Trajectory Optimization with the Particle Swarm Optimisation

Commercial Aircraft Trajectory Optimization to Reduce Flight Costs and Pollution: Metaheuristic Algorithms

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