A Constraint Programming Approach for Agile Earth Observation Satellite Scheduling Problem

The Agile Earth Observation Satellite (AEOS) is equipped with onboard optical instruments. They take image of the Earth's surface according to the requests of customers. Each imaging request which is called as a task generates a profit but it may not be possible to perform all tasks, due to the presence of several constraints. In this paper we consider the AEOS scheduling problem, in which a subset of requests from a given set of tasks is selected to maximize profit. We propose a constraint programming (CP) model to solve this NP-hard problem and test the performance of the CP model by solving a set of generated test instances involving 35 to 55 requests. The results show that our model is competitive and can find optimum solutions in reasonable computation times.