Three-Stage Based Hybrid Metaheuristic Algorithm for Agile Satellites Joint Imaging and Data Transmission Scheduling

As the observation data generated by Earth Observation Satellites (EOSs) increase, the joint scheduling of satellite imaging and data transmission has become a bottleneck in EOS resource applications. This study has proposed a three-stage-based hybrid meta-heuristic scheduling algorithm for the Agile Satellite Joint Imaging and Data Transmission Scheduling (ASJIDTS) problem. The original complex problem is decomposed into three distinct phases: joint task allocation for imaging and data transmission, scheduling of imaging tasks, and scheduling data transmission tasks. During the initial phase of joint task allocation, both imaging and data transmission resources are preemptively allocated using a greedy-based strategy, which considers data transmission opportunities, the conflict degree, and the spatial distribution of different resources. Subsequently, the imaging task scheduling phase generates an optimized sequence for imaging tasks. Based on this sequence, a rule-based multi-insertion strategy for the data transmission scheduling phase has been designed, which ensures rapid responsiveness to data transmission tasks. Extensive experiments have been conducted to verify the proposed algorithm. For the scheduling scenarios with 200 tasks, The Hybrid Metaheuristic Algorithm based on Multi-Stage (HMA-MS) shows at least a 14.11% increase in scheduling profit compared to several excellent algorithms. The experimental results validate the superior capability of the proposed algorithm in handling large-scale scheduling problems.