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Low-Thrust Orbit Transfer Optimization using a Combined Method

by R. Esmaelzadeh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 89 - Number 4
Year of Publication: 2014
Authors: R. Esmaelzadeh
10.5120/15491-4284

R. Esmaelzadeh . Low-Thrust Orbit Transfer Optimization using a Combined Method. International Journal of Computer Applications. 89, 4 ( March 2014), 20-24. DOI=10.5120/15491-4284

@article{ 10.5120/15491-4284,
author = { R. Esmaelzadeh },
title = { Low-Thrust Orbit Transfer Optimization using a Combined Method },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 89 },
number = { 4 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 20-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume89/number4/15491-4284/ },
doi = { 10.5120/15491-4284 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:08:23.513422+05:30
%A R. Esmaelzadeh
%T Low-Thrust Orbit Transfer Optimization using a Combined Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 89
%N 4
%P 20-24
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A genetic algorithm is used together with calculus of variations to optimize an interplanetary trajectory for the Bryson-Ho Earth-to-Mars orbit transfer problem. The global search properties of genetic algorithm combine with the local search capabilities of calculus of variations to produce solutions that are superior to those generated with the calculus of variations alone, and these solutions require less user interaction than previously possible. The genetic algorithm is not hampered by ill-behaved gradients and is relatively insensitive to problems with a small radius of convergence, allowing it to optimize trajectories for which solutions had not yet been obtained. The use of the calculus of variations within the genetic algorithm optimization routine increased the precision of the final solution to levels uncommon for a genetic algorithm.

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Index Terms

Computer Science
Information Sciences

Keywords

Trajectory optimization Genetic algorithms Hybrid methods Orbit transfer.

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