Application of Genetic Algorithm for Preliminary Trajectory Optimization

Pervier, Hugo; Nalianda, Devaiah; Espi, Ramon; Sethi, Vishal; Pilidis, Pericles; Zammit-Mangion, David; Rogero, Jean-Michel; Entz, Ricardo

doi:10.4271/2011-01-2594

Cited by 11 publications

(7 citation statements)

References 3 publications

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“…The most desired quality of EA is therefore that they are natively suitable for the research of the global optima, since the method produces an arbitrary number of non-deterministic initial guesses and the algorithm itself is not restricted on the concept of the search scope. Among other research activities, EA were exploited as part of the research within the Systems for Green Operations Integrated Technology Demonstrator (SGO-ITD) of Clean Sky by the Green Systems for Aircraft Foundation (GSAF) academic cluster [122][123][124][125][126][127][128][129][130][131][132][133].…”

Section: Heuristic Methodsmentioning

confidence: 99%

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

Gardi

Sabatini

Ramasamy

2016

Progress in Aerospace Sciences

116

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The continuous increase of air transport demand worldwide and the push for a more economically viable and environmentally sustainable aviation are driving significant evolutions of aircraft, airspace and airport systems design and operations. Although extensive research has been performed on the optimisation of aircraft trajectories and very efficient algorithms were widely adopted for the optimisation of vertical flight profiles, it is only in the last few years that higher levels of integration were proposed for automated flight planning and rerouting functionalities of innovative Communication Navigation and Surveillance/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) systems. In this context, the implementation of additional environmental targets and of multiple operational constraints introduces the need to efficiently deal with multiple objectives as part of the trajectory optimisation algorithm. This article provides a comprehensive review of Multi-Objective Trajectory Optimisation (MOTO) techniques for transport aircraft flight operations, with a special focus on the recent advances introduced in the CNS+A research context. In the first section, a brief introduction is given, together with an overview of the main international research initiatives where this topic has been studied, and the problem statement is given. The second section introduces the mathematical formulation and the third section reviews the numerical solution techniques, including discretisation and optimisation methods for the specific problem formulated. The fourth section summarises the strategies to articulate the preferences and to select optimal trajectories when multiple conflicting objectives are introduced. The fifth section introduces a number of models defining the optimality criteria and constraints typically adopted in MOTO studies, including fuel consumption, air pollutant and noise emissions, operational costs, condensation trails, current airspace and airport operations. A brief overview of atmospheric and weather modelling is also included. Key equations describing the optimality criteria are presented, with a focus on the latest advancements in the respective application areas. In the sixth section, a number of MOTO implementations in the CNS+A systems context are mentioned with relevant simulation case studies addressing different operational tasks. The final section draws some conclusions and outlines guidelines for future research on MOTO and associated CNS+A system implementations.

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Section: Heuristic Methodsmentioning

confidence: 99%

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

Gardi

Sabatini

Ramasamy

2016

Progress in Aerospace Sciences

116

View full text Add to dashboard Cite

show abstract

“…Pervier et al [19] and Torres et al [20] treated the problem of calculating Pareto optimal fronts between environmental objectives as a discrete parameter optimization problem with bounded variables to maintain feasibility. However, the search for the Pareto front can be treated as an multiobjective optimal control problem.…”

Section: Trajectory Optimizationmentioning

confidence: 99%

Multiobjective Environmental Departure Procedure Optimization

McEnteggart

Whidborne

2018

Journal of Aircraft

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To achieve a sustainable future for air transport, the International Civil Aviation Organization has proposed goals for reductions in community noise impact, local air quality and climate impacting emissions. The paper focuses on the contribution aircraft operations make to those goals. It describes a multiobjective optimisation methodology intended to support the planning of environmentally efficient departure procedures. The methodology treats the problem as a multiobjective optimal control problem that is solved through the application of a direct method of trajectory optimisation and a multiobjective version of the Differential Evolution algorithm. The method generates Pareto fronts between several competing objectives allowing the decision maker to make informed decisions about potential trade-offs between different environmental goals. The methodology is demonstrated through its application to a real world many objective procedure optimisation study. The method supported in depth analysis of the problem not achievable through existing methods and was used to identify a solutions set that offered improvements in all environmental objectives relative to the existing procedure design.

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“…GATAC trajectory optimisation software framework was used to run the simulation. GATAC has a set of optimisers which include a genetic-based optimiser called NSGAMO, and a multi-objective tabu search (MOTS) and also a hybrid optimiser [26,27]. For this study, the NSGAMO was used.…”

Section: Framework and Optimiser Setupmentioning

confidence: 99%

Improving the operating efficiency of the more electric aircraft concept through optimised flight procedures

2018

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The increasing awareness of the environmental risks and costs due to the growing demand in aviation has prompted both academic and industrial research into short-term and long-term technologies which could help address the challenges. Among these, the more electric aircraft has been identified as a key design concept which would make aircraft more environmentally friendly and cost effective in the long run. Moreover, the notion of free-flight and optimised trajectories has been identified as a key operational concept which would help curb the environmental effects of aircraft as well as reduce overall costs. The research in this paper presents a methodology in which these two concepts can be coupled to study the benefits of more electric aircraft (MEA) flying optimised trajectories. A wide range of issues from aircraft performance, engine performance, airframe systems operation, power off-take penalties, emission modelling, optimisation algorithms and optimisation frameworks has been addressed throughout the study. The case study is based on a popular short haul flight between London Heathrow and Amsterdam Schiphol. The culmination of the study establishes the advantage of the MEA over conventional aircraft and also addresses the enhanced approach to the classical aircraft trajectory optimisation problem. The study shows that the operation procedures to achieve a minimum fuel burn are significantly different for a conventional aircraft and MEA. Trajectory optimisation reduced the fuel burn by 17.4% for the conventional aircraft and 12.2% for the more electric compared to the respective baseline cases. Within the constraints of the study, the minimum fuel burn trajectory for the MEA consumed 9.9% less fuel than the minimum fuel burn trajectory for the conventional aircraft.

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Application of Genetic Algorithm for Preliminary Trajectory Optimization

Cited by 11 publications

References 3 publications

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

Multiobjective Environmental Departure Procedure Optimization

Improving the operating efficiency of the more electric aircraft concept through optimised flight procedures

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