The task scheduling model and algorithm for imaging satellites with optimizing satellite service life

Complicated collaborative tasks can be performed by networking satellites, and the resource cost and the scheduling risk can also be optimized by building an effective task-scheduling model. This paper describe three respects of the work. First, the goal programming model is established to describe the resource usage expectations, made by satellite experts in view of satellite service life. Second, a task scheduling model is established to optimize the task gains, the resource cost and the scheduling risk. Third, a gene algorithm and a tabu algorithm are combined to solve the model, since the scheduling problem is an NP-hard problem; furthermore, the solving algorithm is extended by neighbor greedy search to improve the convergence rate and robustness of the algorithm. Finally, a distributed parallel method is adopted to improve the effectiveness.