A Simulated Annealing Algorithm for Ground Station Scheduling Problem

Among different versions of Satellite Scheduling, there is the Ground Station Scheduling, whose aim is mission allocation of ground stations to spacecrafts. This scheduling problem belongs to the family of scheduling with time windows, and besides complexities of classical scheduling problems, it has additional requirements that make it over-constrained and challenging to solve to optimality. In fact, in some cases it is even hard to find a feasible solution that satisfies all user requirements and resource constraints. As with other computationally hard combinatorial optimization problems, heuristic solutions are employed to find high quality solutions in reasonable amount of computation time. In this paper we present a Simulated Annealing (SA) algorithm for the problem, which is a local search based algorithm that simulates the cooling process by gradually lowering the temperature of the system until it converges to a stable state. The Satellite Toolkit is used for the experimental study and performance evaluation of the algorithm through a family of instances of small, medium and large sizes.