Multi-disciplinary optimization of constellation deployment strategies including launcher selection

Last decade's rapid growth of satellite constellation size has led to performance boosts and it has enabled unprecedented applications. However, this enlargement poses several challenges, especially related to their deployment and their economic viability. The problem is inherently multi-disciplinary and requires complex methods to explore its trade-space effectively. This work proposes a hybrid multi-objective method to concurrently select the optimal combination of launch opportunities and maneuvering strategies which minimizes time and cost. The method, using a combination of mixed-integer programming and heuristic optimization algorithms, allows for effective exploration of the coupling variables of the problem, thanks to the exploitation of the on-board propulsion and detailed launcher performance models. The results are applied to a set of case studies, comprising Starlink and a CubeSat constellation, demonstrating the capabilities of the methodology and its breadth of applicability in finding optimal deployment strategies including the launchers selection.