Mathematical Models and Reinforcement Learning based Evolutionary Algorithm Framework for Satellite Scheduling Problem

Yanjie Song
1/7/2023
cs.NEcs.AImath.OC

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Abstract

For complex combinatorial optimization problems, models and algorithms are at the heart of the solution. The complexity of many types of satellite mission planning problems is NP-hard and places high demands on the solution. In this paper, two types of satellite scheduling problem models are introduced and a reinforcement learning based evolutionary algorithm framework based is proposed.

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Cite this paper

@article{song2023mathematical,
  title  = {Mathematical Models and Reinforcement Learning based Evolutionary Algorithm Framework for Satellite Scheduling Problem},
  author = {Yanjie Song},
  year   = {2023},
  eprint = {2301.02764},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2301.02764v3}
}

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