Memetic strategies for global trajectory optimisation

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)

Abstract

Some types of space trajectory design problems present highly multimodal, globally non-convex objective functions with a large number of local minima, often nested. This paper proposes some memetic strategies to improve the performance of the basic heuristic of differential evolution when applied to the solution of global trajectory optimisation. In particular, it is often more useful to find families of good solutions rather than a single, globally optimal one. A rigorous testing procedure is introduced to measure the performance of a global optimisation algorithm. The memetic strategies are tested on a standard set of difficult trajectory optimisation problems.
Original languageEnglish
Title of host publicationAdvances in Computation and Intelligence
Place of PublicationBerlin
Pages180-190
Volume5821
DOIs
Publication statusPublished - 2009

Publication series

NameLecture Notes in Computer Science
PublisherSpringer-Verlag, Berlin
Volume5821
ISSN (Print)0302-9743

Keywords

  • global trajectory optimisation
  • memetics

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