Integrated space logistics mission planning and spacecraft design with mixed-integer nonlinear programming

This paper develops a campaign-level space logistics optimization framework that simultaneously considers mission planning and spacecraft design using mixed-integer nonlinear programming. In the mission planning part of the framework, deployment and utilization of in-orbit infrastructures, such as in-orbit propellant depots or in situ resource utilization plants, are also taken into account.Two methods are proposed: First, the mixed-integer nonlinear programming problem is converted into a mixed-integer linear programming problem after approximating the nonlinear model with a piecewise linear function and linearizing quadratic terms. In addition, another optimization framework is provided, based on simulated annealing, which separates the spacecraft model from mission planning formulation. An example mission scenario based on multiple Apollo missions is considered, and the results show a significant improvement in the initial mass in low Earth orbit by campaign-level design as compared with the traditional mission-level design. It is also shown that the mixed-integer linear programming-based method gives better-quality solutions than the simulated annealing-based method, although the simulated annealing method is more flexible for extension to a higher-fidelity spacecraft model.