Abstract

This paper describes a combined genetic algorithm for selecting and scheduling tasks of agile earth observing satellites (AEOS). This kind of satellite has three degrees of freedom for acquiring images, and giving opportunities for a more efficient use of the satellite imaging capabilities. But the selection and scheduling of observations becomes significantly difficult, due to the larger search space for potential solutions. Hence, selecting and scheduling observations of agile satellites is a highly combinatorial problem. Inspired by successful commercial applications of evolutionary algorithms in scheduling domains, this paper presents work in progress regarding the use of combined genetic algorithm to solve it. Both the model problems and the algorithm are described. The validity of this approach is validated by emulations.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.