Scheduling earth observation activities in LEO satellites using graph coloring problem

Abstract

Scheduling system of low earth orbit (LEO) satellite operations is one of the important tasks performed in satellites. Satellite specific constraints, satellite priorities, revenue of certain payloads and special operations, as well as visibility conflicts are taken into consideration while generating the operations schedules in an optimum way. This paper uses graph coloring problem for earth observation satellite scheduling, where as earth observing operations have to be scheduled on several resources while respecting time constraint and taking the revenue of the operations into account with the objective of scheduling as many operations as possible within its time window. Then a tabu search heuristic is proposed for this coloring problem. The computational results indicate that this approach is typically effective to generate a near optimal and feasible schedule for imaging operations of the satellite.

A Heuristic Algorithm Based on Temporal Conflict Network for Agile Earth Observing Satellite Scheduling Problem

“…Zufferey et al [19] adapted the best ingredients of the graph coloring techniques to the NP-hard satellite range scheduling problem, called MuRRSP, then a tabu search and an adaptive memory algorithm were designed to tackle it. Sarkheyli et al [20] followed this line in investigating the scheduling system of low earth orbit (LEO) satellite operations. Wang et al [21] firstly introduced the theory of complex networks and found similarities between AEOS redundant targets scheduling problem and the node centrality ranking problem, then proposed a fast approximate scheduling algorithm (FASA) to obtain effective scheduling results.…”