@inbook{019930ebe94844ea8acc34164af6a205,
title = "Search space pruning and global optimization of multiple gravity assist trajectories with deep space manoeuvres",
abstract = "This paper deals with the design of optimal multiple gravity assist trajectories with deep space manoeuvres. A pruning method which considers the sequential nature of the problem is presented. The method locates feasible vectors using local optimization and applies a clustering algorithm to find reduced bounding boxes which can be used in a subsequent optimization step. Since multiple local minima remain within the pruned search space, the use of a global optimization method, such as Differential Evolution, is suggested for finding solutions which are likely to be close to the global optimum. Two case studies are presented.",
author = "Becerra, {V. M.} and Nasuto, {S. J.} and J. Anderson and M. Ceriotti and C. Bombardelli",
note = "Proceedings Paper IEEE Congress on Evolutionary Computation SEP 25-28, 2007 Singapore, SINGAPORE",
year = "2007",
language = "English",
series = "IEEE Congress on Evolutionary Computation",
publisher = "IEEE/ IAPR",
pages = "957--964",
booktitle = "2007 IEEE Congress on Evolutionary Computation, Vols 1-10, Proceedings",
}