Title :
Task scheduling on spacecraft by hybrid genetic algorithms
Author :
Jeong, Il-Jun ; Papavassilopoulos, George ; Bayard, David S.
Author_Institution :
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
A genetic algorithm is developed for scheduling task on a spacecraft having constrained resources. Due to the complex nature of the constraints, it is necessary to take a hybrid approach where the genetic algorithm is combined with a decoder routine to generate feasible solutions. The performance of the hybrid algorithm is demonstrated by example. Results are very encouraging, demonstrating an improvement relative to earlier results, and providing a flexible capability to modify existing sequences in near-real-time to comply with time-varying goals and constraints
Keywords :
aerospace computing; genetic algorithms; scheduling; space vehicles; constrained resources; decoder routine; genetic algorithm; spacecraft; task scheduling; time-varying goals; Decoding; Delay; Genetic algorithms; Genetic mutations; Hybrid power systems; Laboratories; Processor scheduling; Propulsion; Space technology; Space vehicles;
Conference_Titel :
Robotics and Automation, 1999. Proceedings. 1999 IEEE International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-5180-0
DOI :
10.1109/ROBOT.1999.770017