Zhai Xuejun;Niu Xiaonan;Tang Hong;Wu Lixin;Shen Yonglin;

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

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

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

[Shen, Yonglin] China Univ Geosci, Fac Informat Engn, Wuhan 430074, Peoples R China.

ABSTRACT:  Earth observation satellites play a significant role in rapid responses to emergent events on the Earth's surface, for example, earthquakes. In this paper, we propose a robust satellite scheduling model to address a sequence of emergency tasks, in which both the profit and robustness of the schedule are simultaneously maximized in each stage. Both the multiobjective genetic algorithm NSGA2 and rule-based heuristic algorithm are employed to obtain solutions of the model. NSGA2 is used to obtain a flexible and highly robust initial schedule. When every set of emergency tasks arrives, a combined algorithm called HA-NSGA2 is used to adjust the initial schedule. The heuristic algorithm (HA) is designed to insert these tasks dynamically to the waiting queue of the initial schedule. Then the multiobjective genetic algorithm NSGA2 is employed to find the optimal solution that has maximum revenue and robustness. Meanwhile, to improve the revenue and resource utilization, we adopt a compact task merging strategy considering the duration of task execution in the heuristic algorithm. Several experiments are used to evaluate the performance of HA-NSGA2. All simulation experiments show that the performance of HA-NSGA2 is significantly improved.

Published in MATHEMATICAL PROBLEMS IN ENGINEERING.2015,, DOI: 10.1155/2015/482923