Evolutionary search for deep-space science mission orbits

Pini Gurfil, N. Jeremy Kasdin

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


We present an application of an evolutionary programming method, niching genetic algorithms, to the search for orbits in the spatial elliptic restricted three-body problem (ER3BP) that is suitable for deep-space science missions. The niching method used is deterministic crowding, which renders a global optimization while permitting for several optimal and suboptimal solutions to coexist. This novel approach yields diverse probing of the state space of the ER3BP. From the practical standpoint, the orbits found remain within a bounded distance from Earth, thus allowing high data-rate communication while ensuring safe operational environment, far from thermal perturbations and visual occultation as well as Earth's magnetic and radiation fields.

Original languageEnglish (US)
Pages (from-to)332-341
Number of pages10
JournalJournal of Guidance, Control, and Dynamics
Issue number2
StatePublished - 2006

All Science Journal Classification (ASJC) codes

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


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