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 |
| Keywords: | multigravity assist trajectory design, ant colony optimization algorithm, planning, Mechanical engineering and machinery, Motor vehicles. Aeronautics. Astronautics |
| Subjects: | Technology > Mechanical engineering and machinery Technology > Motor vehicles. Aeronautics. Astronautics |
| Department: | Faculty of Engineering > Mechanical and Aerospace Engineering |
| Related URLs: | |
| Depositing user: | Ms Katrina May |
| Date Deposited: | 21 Jul 2010 10:15 |
| Last modified: | 12 Dec 2012 10:35 |
| URI: | http://strathprints.strath.ac.uk/id/eprint/26352 |
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