Aiming at the operation support scheduling of carrier-based aircraft, this paper proposes a scheduling optimization algorithm based on apprenticeship learning which can quickly generate a operation support schedule for a carrier-based aircraft fleet.

Using the apprenticeship learning method, the executed and unexecuted tasks in expert demonstrations are compared in pairs to construct a sample set, and the support task scheduling classifier is trained based on the deck features of aircraft carrier. On this basis, a support task apprenticeship learning algorithm for a carrier-based aircraft fleet is designed and compared with the traditional genetic algorithm （GA） in terms of solving solution, solving time and resource allocation.

The results show that the operation support schedule obtained by the apprenticeship scheduling algorithm is equivalent to that by the traditional GA, but the rate of convergence is increased nearly fourfold, and the support resources are more evenly distributed.

The apprenticeship scheduling algorithm proposed in this paper can adequately learn from expert experiences and solve the problem of static single-objective carrier-based aircraft support scheduling. As such, this study provides references for further research in the field of dynamic multi-objective carrier-based aircraft support scheduling.