TY - GEN
T1 - Optimal space trajectories via particle swarm technique
AU - Pontani, Mauro
AU - Conway, Bruce A.
PY - 2010
Y1 - 2010
N2 - The particle swarm optimization technique is a population-based stochastic method developed in recent years and successfully applied in several fields of research. It represents a very intuitive (and easy to program) methodology for global optimization, inspired by the behavior of bird flocks while searching for food. The particle swarm optimization technique attempts to take advantage from the mechanism of information sharing that affects the overall behavior of a swarm, with the intent of determining the optimal values of the unknown parameters of the problem under consideration. In this research the method is applied to a variety of space trajectory optimization problems, e.g. the determination of periodic orbits in the context of the circular restricted three-body problem, and the optimization of (impulsive and finite-thrust) orbital transfers. Despite its simplicity and intuitiveness, the particle swarm algorithm proves to be quite effective in finding the optimal solution to all of the applications considered in the paper, with great numerical accuracy.
AB - The particle swarm optimization technique is a population-based stochastic method developed in recent years and successfully applied in several fields of research. It represents a very intuitive (and easy to program) methodology for global optimization, inspired by the behavior of bird flocks while searching for food. The particle swarm optimization technique attempts to take advantage from the mechanism of information sharing that affects the overall behavior of a swarm, with the intent of determining the optimal values of the unknown parameters of the problem under consideration. In this research the method is applied to a variety of space trajectory optimization problems, e.g. the determination of periodic orbits in the context of the circular restricted three-body problem, and the optimization of (impulsive and finite-thrust) orbital transfers. Despite its simplicity and intuitiveness, the particle swarm algorithm proves to be quite effective in finding the optimal solution to all of the applications considered in the paper, with great numerical accuracy.
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M3 - Conference contribution
AN - SCOPUS:80053390846
SN - 9780877035602
T3 - Advances in the Astronautical Sciences
SP - 53
EP - 72
BT - Spaceflight Mechanics 2010 - Advances in the Astronautical Sciences
T2 - AAS/AIAA Space Flight Mechanics Meeting
Y2 - 14 February 2010 through 17 February 2010
ER -