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 language | English (US) |
|---|---|
| Pages (from-to) | 196-198 |
| Number of pages | 3 |
| Journal | Journal of Guidance, Control, and Dynamics |
| Volume | 20 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1997 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Aerospace Engineering
- Space and Planetary Science
- Electrical and Electronic Engineering
- Applied Mathematics
Fingerprint
Dive into the research topics of 'Near-optimal low-thrust trajectories via micro-genetic algorithms'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS