Title :
A Decomposition-Based Algorithm for Imaging Satellites Scheduling Problem
Author :
Li Jufang ; Yao Feng ; Bai Baocun ; He Renjie
Author_Institution :
Coll. of Inf. Syst. & Manage., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
A decomposition-based optimization algorithm was proposed for solving imaging satellites scheduling problem. The problem was decomposed into task assignment main problem and single satellite scheduling sub-problem. In task assignment phase, the tasks were allocated to the satellites, and each satellite would schedule the task respectively in single satellite scheduling phase. We adopted an adaptive ant colony optimization algorithm to search the optimal task assignment scheme. A heuristic algorithm and a very fast simulated annealing algorithm were used to solve the single satellite scheduling problem. The task assignment scheme was valued by integrating the observation scheduling result of multiple satellites,and the result was responded to the ant colony optimization algorithm to guide the search process. Experiment results showed that the approach was effective.
Keywords :
artificial satellites; image processing; scheduling; search problems; simulated annealing; adaptive ant colony optimization algorithm; decomposition-based algorithm; decomposition-based optimization algorithm; heuristic algorithm; imaging satellites scheduling problem; observation scheduling; optimal task assignment scheme; search process; simulated annealing algorithm; single satellite scheduling phase; single satellite scheduling problem; task allocation; task assignment phase; Ant colony optimization; Helium; Heuristic algorithms; Processor scheduling; Satellites; Scheduling algorithm; Simulated annealing; Single machine scheduling; Switches; Time factors;
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
DOI :
10.1109/ICIECS.2009.5363469