A Large-Scale Scheduling Method for Multiple Agile Optical Satellites

This study investigates the scheduling problem of multiple agile optical satellites with large-scale tasks. This problem is difficult to solve owing to the time-dependent characteristic of agile optical satellites, complex constraints, and considerable solution space. To solve the problem, we propose a scheduling method based on an improved sine and cosine algorithm and a task merging approach. We first establish a scheduling model with task merging constraints and observation action constraints to describe the problem. Then, an improved sine and cosine algorithm is proposed to search for the optimal solution with the maximum profit ratio. An adaptive cosine factor and an adaptive greedy factor are adopted to improve the algorithm. Besides, a task merging method with a task reallocation mechanism is developed to improve the scheduling efficiency. Experimental results demonstrate the superiority of the proposed algorithm over the comparison algorithms.