Mathematical Models and Reinforcement Learning based Evolutionary Algorithm Framework for Satellite Scheduling Problem
This addresses satellite mission planning for aerospace applications, but appears incremental as it combines existing methods without clear breakthroughs.
The paper tackles the NP-hard satellite scheduling problem by introducing two mathematical models and proposing a reinforcement learning based evolutionary algorithm framework, but no concrete results or numbers are provided.
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.