Search space pruning and global optimization of multiple gravity assist trajectories with deep space manoeuvres

V. M. Becerra, S. J. Nasuto, J. Anderson, M. Ceriotti, C. Bombardelli

    Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

    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.
    Original languageEnglish
    Title of host publication2007 IEEE Congress on Evolutionary Computation, Vols 1-10, Proceedings
    Place of PublicationNew York
    PublisherIEEE/ IAPR
    Pages957-964
    Number of pages8
    Publication statusPublished - 2007

    Publication series

    NameIEEE Congress on Evolutionary Computation
    PublisherIEEE

    Fingerprint

    Dive into the research topics of 'Search space pruning and global optimization of multiple gravity assist trajectories with deep space manoeuvres'. Together they form a unique fingerprint.

    Cite this