The scheduling problem of an earth observation satellite is a large and difficult combinatorial optimization problem. Thankfully, such a scheduling problem is well-studied with numerous papers stating different problem formulations.

Mar 1, 2023 · The proposed DRL-based algorithm solves the assignment problem, and the heuristic algorithm deals with the single antenna scheduling problem. It is concluded from the experimental comparison and analysis that the combination of DRL-based and the heuristic algorithm can effectively deal with SRSP.

The energy-efficient satellite range scheduling problem (EESRSP) aims to optimize task sequencing profits within the satellite management system while simultaneously conserving energy. To address this problem, a mixed-integer scheduling model is constructed, taking into account the energy consumption of ground stations during telemetry ...

Jun 18, 2021 · In this paper, inspired by the success of deep reinforcement learning in optimization domains, the deep deterministic policy gradient algorithm is adopted to solve a time-continuous satellite task scheduling problem.

In this paper, we present and analyse some relevant formulations of the satellite scheduling viewed as a family of problems and identify various forms of optimization objectives. The main complexities, due highly constrained nature, windows accessibility and visibility, multi-objectives and conflicting objectives are examined.

Jan 18, 2025 · Finally, the end-to-end route is determined using the Dijkstra algorithm. We consider several key factors including the connection distance, rotational velocity, link setup time, and link switching frequency.

problem. The satellite scheduling problem is a real-world com-binational optimization problem that models satellite resources and tasks and then maximizes their benefits via optimization algorithms, subject to certain constraint conditions. Compared with classical combinational opti-

Oct 18, 2023 · At present, the research of SRSP mainly focuses on the algorithm improvement under different scheduling scenarios and the simulation optimization of real cases. This paper focuses on SRSP and is organized as follows. Section 1 introduces the definition, classification and development of SRSP.

4 days ago · Additionally, Li et al. (2022) proposed a multi-satellite telemetry and command resource scheduling strategy based on deep neural networks, and Liu et al. (2021) improved the EOS problem for low Earth orbit satellite networks using dendritic neural networks. The combination of traditional heuristic algorithms with reinforcement learning ...

To reduce the route change as much as possible during the periodical topology change, in this work, we refined the original Dijkstra and propose StableRoute to select the most appropriate route from the equal-cost candidates with the least route updates compared with the …