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Search space pruning and global optimisation of multiple gravity assist spacecraft trajectories

Research output: Contribution to journalArticle

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Search space pruning and global optimisation of multiple gravity assist spacecraft trajectories. / Izzo, D.; Becerra, V. M.; Myatt, D. R.; Nasuto, S. J.; Bishop, J. M.

In: Journal of Global Optimization, Vol. 38, No. 2, 22.11.2007, p. 283-296.

Research output: Contribution to journalArticle

Harvard

Izzo, D, Becerra, VM, Myatt, DR, Nasuto, SJ & Bishop, JM 2007, 'Search space pruning and global optimisation of multiple gravity assist spacecraft trajectories', Journal of Global Optimization, vol. 38, no. 2, pp. 283-296. <http://centaur.reading.ac.uk/15293/>

APA

Izzo, D., Becerra, V. M., Myatt, D. R., Nasuto, S. J., & Bishop, J. M. (2007). Search space pruning and global optimisation of multiple gravity assist spacecraft trajectories. Journal of Global Optimization, 38(2), 283-296. http://centaur.reading.ac.uk/15293/

Vancouver

Izzo D, Becerra VM, Myatt DR, Nasuto SJ, Bishop JM. Search space pruning and global optimisation of multiple gravity assist spacecraft trajectories. Journal of Global Optimization. 2007 Nov 22;38(2):283-296.

Author

Izzo, D. ; Becerra, V. M. ; Myatt, D. R. ; Nasuto, S. J. ; Bishop, J. M. / Search space pruning and global optimisation of multiple gravity assist spacecraft trajectories. In: Journal of Global Optimization. 2007 ; Vol. 38, No. 2. pp. 283-296.

Bibtex

@article{bbc385a4b5b242bd9b6296e6617beb63,
title = "Search space pruning and global optimisation of multiple gravity assist spacecraft trajectories",
abstract = "We introduce and describe the Multiple Gravity Assist problem, a global optimisation problem that is of great interest in the design of spacecraft and their trajectories. We discuss its formalization and we show, in one particular problem instance, the performance of selected state of the art heuristic global optimisation algorithms. A deterministic search space pruning algorithm is then developed and its polynomial time and space complexity derived. The algorithm is shown to achieve search space reductions of greater than six orders of magnitude, thus reducing significantly the complexity of the subsequent optimisation.",
keywords = "Multiple Gravity Assist, space pruning, constraint propagation, differential evolution, particle swarm, genetic algorithm, GASP, global, trajectory optimisation",
author = "D. Izzo and Becerra, {V. M.} and Myatt, {D. R.} and Nasuto, {S. J.} and Bishop, {J. M.}",
year = "2007",
month = nov,
day = "22",
language = "English",
volume = "38",
pages = "283--296",
journal = "Journal of Global Optimization",
issn = "0925-5001",
publisher = "Springer Netherlands",
number = "2",

}

RIS

TY - JOUR

T1 - Search space pruning and global optimisation of multiple gravity assist spacecraft trajectories

AU - Izzo, D.

AU - Becerra, V. M.

AU - Myatt, D. R.

AU - Nasuto, S. J.

AU - Bishop, J. M.

PY - 2007/11/22

Y1 - 2007/11/22

N2 - We introduce and describe the Multiple Gravity Assist problem, a global optimisation problem that is of great interest in the design of spacecraft and their trajectories. We discuss its formalization and we show, in one particular problem instance, the performance of selected state of the art heuristic global optimisation algorithms. A deterministic search space pruning algorithm is then developed and its polynomial time and space complexity derived. The algorithm is shown to achieve search space reductions of greater than six orders of magnitude, thus reducing significantly the complexity of the subsequent optimisation.

AB - We introduce and describe the Multiple Gravity Assist problem, a global optimisation problem that is of great interest in the design of spacecraft and their trajectories. We discuss its formalization and we show, in one particular problem instance, the performance of selected state of the art heuristic global optimisation algorithms. A deterministic search space pruning algorithm is then developed and its polynomial time and space complexity derived. The algorithm is shown to achieve search space reductions of greater than six orders of magnitude, thus reducing significantly the complexity of the subsequent optimisation.

KW - Multiple Gravity Assist, space pruning, constraint propagation, differential evolution, particle swarm, genetic algorithm, GASP, global, trajectory optimisation

M3 - Article

VL - 38

SP - 283

EP - 296

JO - Journal of Global Optimization

JF - Journal of Global Optimization

SN - 0925-5001

IS - 2

ER -

ID: 3262075