Niu Xiaonan;Tang Hong;Wu Lixin;Deng Run;Zhai Xuejun;

 

[Niu, Xiaonan; Tang, Hong; Deng, Run; Zhai, Xuejun] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China.

[Niu, Xiaonan; Tang, Hong; Deng, Run; Zhai, Xuejun] Beijing Normal Univ, Key Lab Environm Change & Nat Disaster, Minist Educ, Beijing 100875, Peoples R China.

[Wu, Lixin] China Univ Min & Technol, Sch Environm Sci & Spatial Informat, Xuzhou 221116, Peoples R China.

 

ABSTRACT: We present novel two-stage dynamic scheduling of earth observation satellites to provide emergency response by making full use of the duration of the imaging task execution. In the first stage, the multiobjective genetic algorithm NSGA-II is used to produce an optimal satellite imaging schedule schema, which is robust to dynamic adjustment as possible emergent events occur in the future. In the second stage, when certain emergent events do occur, a dynamic adjusting heuristic algorithm (CTM-DAHA) is applied to arrange new tasks into the robust imaging schedule. Different from the existing dynamic scheduling methods, the imaging duration is embedded in the two stages to make full use of current satellite resources. In the stage of robust satellite scheduling, total task execution time is used as a robust indicator to obtain a satellite schedule with less imaging time. In other words, more imaging time is preserved for future emergent events. In the stage of dynamic adjustment, a compact task merging strategy is applied to combine both of existing tasks and emergency tasks into a composite task with least imaging time. Simulated experiments indicate that the proposed method can produce a more robust and effective satellite imaging schedule.

Published in MATHEMATICAL PROBLEMS IN ENGINEERING. 2015, DOI: 10.1155/2015/731734