  The Earth observation satellites (EOSs) are specially designed to collect
images according to user requirements. The agile EOSs (AEOS), with stronger
attitude maneuverability, greatly improve the observation capability, while
increasing the complexity in scheduling. We address a multiple AEOSs scheduling
with multiple observations for the first time}, where the objective function
aims to maximize the entire observation profit over a fixed horizon. The profit
attained by multiple observations for each target is nonlinear to the number of
observations. We model the multiple AEOSs scheduling as a specific interval
scheduling problem with each satellite orbit respected as machine. Then A
column generation based framework is developed to solve this problem, in which
we deal with the pricing problems with a label-setting algorithm. Extensive
simulations are conducted on the basis of a China's AEOS constellation, and the
results indicate the optimality gap is less than 3% on average, which validates
the performance of the scheduling solution obtained by the proposed framework.
We also compare the framework in the conventional EOS scheduling.
