Near-optimal low-thrust trajectories via micro-genetic algorithms

Research output: Contribution to journalArticle

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Abstract

The use of micro-genetic algorithms to determine near-optimal low-thrust trajectories is studied. Micro-genetic algorithms are inefficient at achieving near optimal solutions when boundary conditions were treated as equality constraints. However, when boundary conditions are cast as inequality constraints, micro-genetic algorithms showed faster convergence than simple genetic algorithms to near-optimal region.

Original languageEnglish (US)
Pages (from-to)196-198
Number of pages3
JournalJournal of Guidance, Control, and Dynamics
Volume20
Issue number1
DOIs
StatePublished - Jan 1 1997
Externally publishedYes

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Aerospace Engineering
  • Space and Planetary Science
  • Electrical and Electronic Engineering
  • Applied Mathematics

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