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Automated multigravity assist trajectory planning with a modified ant colony algorithm

Ceriotti, M. and Vasile, M. (2010) Automated multigravity assist trajectory planning with a modified ant colony algorithm. Journal of Aerospace Computing, Information, and Communication, 7 (9). pp. 261-293. ISSN 1542-9423

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Abstract

The paper presents an approach to transcribe a multigravity assist trajectory design problem into an integrated planning and scheduling problem. A modified Ant Colony Optimization (ACO) algorithm is then used to generate optimal plans corresponding to optimal sequences of gravity assists and deep space manoeuvers to reach a given destination. The modified Ant Colony Algorithm is based on a hybridization between standard ACO paradigms and a tabu-based heuristic. The scheduling algorithm is integrated into the trajectory model to provide a fast time-allocation of the events along the trajectory. The approach demonstrated to be very effective on a number of real trajectory design problems.

Item type: Article
ID code: 26352
Notes: COPYRIGHT OWNED BY ALL AUTHORS
Keywords: multigravity assist trajectory design, ant colony optimization algorithm, planning, Mechanical engineering and machinery, Motor vehicles. Aeronautics. Astronautics, Mechanical Engineering, Aerospace Engineering, Control and Systems Engineering, Computational Mechanics
Subjects: Technology > Mechanical engineering and machinery
Technology > Motor vehicles. Aeronautics. Astronautics
Department: Faculty of Engineering > Mechanical and Aerospace Engineering
Depositing user: Ms Katrina May
Date Deposited: 21 Jul 2010 09:15
Last modified: 21 May 2015 12:53
Related URLs:
URI: http://strathprints.strath.ac.uk/id/eprint/26352

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