Spacecraft design optimization is a difficult problem, due to the complexity of optimization cost surfaces and the human expertise in optimization that is necessary in order to achieve good results. In this paper, we propose the use of a set of generic, metaheuristic optimization algorithms (e.g., genetic algorithms, simulated annealing), which is configured for a particular optimization problem by an adaptive problem solver based on artificial intelligence and machine learning techniques. We describe work in progress on OASIS, a system for adaptive problem solving based on these principles.
Automating the process of optimization in spacecraft design
1997 IEEE Aerospace Conference ; 4 ; 411-427 vol.4
1997-01-01
1555653 byte
Conference paper
Electronic Resource
English
Automating the Process of Optimization in Spacecraft Design
British Library Conference Proceedings | 1997
|Automating the process of estimating spacecraft mass
NTRS | 1980
|Automating Structural Analysis of Spacecraft Vehicles
NTRS | 2004
|Automating Structural Analysis of Spacecraft Vehicles
AIAA | 2004
|