Automatic MGA trajectory planning with a modified ant colony optimization algorithm

M. Ceriotti, M. Vasile

Research output: Contribution to conferencePaper

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Abstract

This paper assesses the problem of designing multiple gravity assist (MGA) trajectories, including the sequence of planetary encounters. The problem is treated as planning and scheduling of events, such that the original mixed combinatorial-continuous problem is discretised and converted into a purely discrete problem with a finite number of states. We propose the use of a two-dimensional trajectory model in which pairs of celestial bodies are connected by transfer arcs containing one deep-space manoeuvre. A modified Ant Colony Optimisation (ACO) algorithm is then used to look for the optimal solutions. This approach was applied to the design of optimal transfers to Saturn and to Mercury, and a comparison against standard genetic algorithm based optimisers shows its effectiveness.
Original languageEnglish
Publication statusPublished - 28 Sep 2009
Event21st International Space Flight Dynamics Symposium, ISSFD 2009 - Toulouse, France
Duration: 28 Sep 20092 Oct 2009

Conference

Conference21st International Space Flight Dynamics Symposium, ISSFD 2009
CityToulouse, France
Period28/09/092/10/09

Fingerprint

Ant colony optimization
Gravitation
Genetic algorithms
Scheduling
Trajectories
Planning

Keywords

  • multiple gravity assist
  • trajectories
  • ant colony optimisation algorithm
  • optimal transfers
  • optimal solutions

Cite this

Ceriotti, M., & Vasile, M. (2009). Automatic MGA trajectory planning with a modified ant colony optimization algorithm. Paper presented at 21st International Space Flight Dynamics Symposium, ISSFD 2009, Toulouse, France, .
Ceriotti, M. ; Vasile, M. / Automatic MGA trajectory planning with a modified ant colony optimization algorithm. Paper presented at 21st International Space Flight Dynamics Symposium, ISSFD 2009, Toulouse, France, .
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Ceriotti, M & Vasile, M 2009, 'Automatic MGA trajectory planning with a modified ant colony optimization algorithm' Paper presented at 21st International Space Flight Dynamics Symposium, ISSFD 2009, Toulouse, France, 28/09/09 - 2/10/09, .

Automatic MGA trajectory planning with a modified ant colony optimization algorithm. / Ceriotti, M.; Vasile, M.

2009. Paper presented at 21st International Space Flight Dynamics Symposium, ISSFD 2009, Toulouse, France, .

Research output: Contribution to conferencePaper

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AB - This paper assesses the problem of designing multiple gravity assist (MGA) trajectories, including the sequence of planetary encounters. The problem is treated as planning and scheduling of events, such that the original mixed combinatorial-continuous problem is discretised and converted into a purely discrete problem with a finite number of states. We propose the use of a two-dimensional trajectory model in which pairs of celestial bodies are connected by transfer arcs containing one deep-space manoeuvre. A modified Ant Colony Optimisation (ACO) algorithm is then used to look for the optimal solutions. This approach was applied to the design of optimal transfers to Saturn and to Mercury, and a comparison against standard genetic algorithm based optimisers shows its effectiveness.

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Ceriotti M, Vasile M. Automatic MGA trajectory planning with a modified ant colony optimization algorithm. 2009. Paper presented at 21st International Space Flight Dynamics Symposium, ISSFD 2009, Toulouse, France, .