With the increasing number of earth observing satellites and the growing demand for remote sensing data, satellite mission scheduling is undergoing a change from the traditional off-line mode to on-line mode. To overcome difficulties in handling large quantities of satellites and large-scale scenes by the current on-line multi-satellite mission scheduling method, we establish the mathematical model, design the computation framework based on multi-agent system contract net protocol. Then we put forward a load reduction method based on mean shift clustering for satellite scheduling agent and a bid evaluation method based on genetic algorithm for central cooperating agent. Finally, Experimental results are used to demonstrate the feasibility and effectiveness of the algorithms.
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