Mathematical Models and Reinforcement Learning based Evolutionary Algorithm Framework for Satellite Scheduling Problem
Neural and Evolutionary Computing
2023-02-02 v3 Artificial Intelligence
Optimization and Control
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.
Cite
@article{arxiv.2301.02764,
title = {Mathematical Models and Reinforcement Learning based Evolutionary Algorithm Framework for Satellite Scheduling Problem},
author = {Yanjie Song},
journal= {arXiv preprint arXiv:2301.02764},
year = {2023}
}
Comments
12 pages. arXiv admin note: substantial text overlap with arXiv:2206.05694