Becerra, V.M., Nasuto, S.J., Anderson, J., Ceriotti, M. and Bombardelli, C. (2007) Search space pruning and global optimization of multiple gravity assist trajectories with deep space manoeuvres. In: IEEE Congress on Evolutionary Computation (CEC 2007), Singapore, China, 25-28 Sep 2007, pp. 957-964. (doi: 10.1109/CEC.2007.4424573)
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Publisher's URL: http://dx.doi.org/10.1109/CEC.2007.4424573
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
Item Type: | Conference Proceedings |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Ceriotti, Dr Matteo |
Authors: | Becerra, V.M., Nasuto, S.J., Anderson, J., Ceriotti, M., and Bombardelli, C. |
College/School: | College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity |
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