Approximate solutions in space mission design

Oliver Schütze, Massimiliano Vasile, Carlos A. Coello Coello

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

8 Citations (Scopus)

Abstract

In this paper, we address multi-objective space mission design problems. We argue that it makes sense from the practical point of view to consider in addition to the 'optimal' trajectories (in the Pareto sense) also approximate or nearly optimal solutions since this can lead to a significant larger variety for the decision maker. For this, we suggest a novel MOEA which is a modification of the well-known NSGA-II algorithm equipped with a recently proposed archiving strategy which aims for the storage of the set of approximate solution of a given MOP. Using this algorithm we will examine several space missions and demonstrate the benefit of the novel approach.
Original languageEnglish
Title of host publicationProceedings of the 10th international conference on Parallel Problem Solving from Nature
Subtitle of host publicationPPSN X
Place of PublicationBerlin
Pages805-814
Number of pages10
Volume5199
DOIs
Publication statusPublished - 13 Sep 2008
Event10th International Conference on Parallel Problem Solving From Nature - Dortmund, Germany
Duration: 13 Sep 200817 Sep 2008

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume5199
ISSN (Print)0302-9743

Conference

Conference10th International Conference on Parallel Problem Solving From Nature
CountryGermany
CityDortmund
Period13/09/0817/09/08

Keywords

  • ant colony optimization
  • artificial life
  • adaptive systems
  • algorithmic learning
  • space mission
  • design solutions

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