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

This paper develops a campaign-level space logistics optimization framework that considers mission planning and spacecraft design simultaneously utilizing mixed integer nonlinear programming (MINP). In the mission planning part of the framework, deployment and utilization of in-orbit infrastructures such as in-orbit propellant depot or in-situ resource utilization (ISRU) plant are also taken into account. Two methods are proposed: First, the MINP is converted into a mixed-integer linear programming (MILP) after approximating the nonlinear model by piecewise function and linearizing quadratic terms. In addition, another optimization framework is provided based on simulated annealing (SA) which separates 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 (IMLEO) by campaign-level design compared with the traditional mission-level design. It is also shown that the SA-based method is harder to achieve global optimum than the MILP-based method in a reasonable time, but it is more flexible for extension to a higher fidelity spacecraft model.