Integrating orbit database and metaheuristics to design satellite constellation

The method we propose is a new approach to the problem of satellite constellation design. The main difficulties of this field are the size of the solution space, the computation time of the optimization criterion and the lack of information to analyse and improve a solution. Our model bypasses some of these obstacles by using an inverse approach where services to be fulfilled are highlighted. The algorithm is composed of different layers solving different problems. We first use the specifications of the services to compensate for lack of information returned by the criterion to analyse and improve a solution. An orbit database introduces an expert knowledge linked to a robust estimator to set consistent orbital parameters. We use a partial evaluation of the constellation to reduce the criterion computation time. The highest level of the algorithm is a metaheuristic layer that drives the search across the wide solution space with a probabilistic tabu search.