  A strategy for the analysis of active debris removal missions targeting
multiple objects from a set of objects in near-circular orbit with similar
inclination is presented. Algebraic techniques successfully reduce the orbital
mechanics regarding specific inter-debris transfer and disposal methods to
simple computations, which can be used as the coefficients of a quadratic
unconstrained binary optimisation (QUBO) problem formulation which minimises
the total propellant used in the mission whilst allowing for servicing time and
meeting the mission deadline. The QUBO is validated by solving artificial small
problems (from 2 to 11 debris) using classical computational methods and the
weaknesses in using these methods are examined prior to solution using quantum
annealing hardware. The quantum processing unit (QPU) and quantum-classical
hybrid solvers provided by D-Wave are then used to solve the same small
problems, with attention paid to evident strengths and weaknesses of each
approach. Hybrid solvers are found to be significantly more effective at
solving larger problems. Finally, the hybrid method is used to solve a large
problem using a real dataset. From a set of 79 debris objects resulting from
the destruction of the Kosmos-1408 satellite, an active debris removal mission
starting on 30 September 2023 targeting 5 debris objects for disposal within a
year with 20 days servicing time per object is successfully planned. This plan
calculates the total propellant cost of transfer and disposal to be 0.87km/s
and would be complete well within the deadline at 241 days from the start date.
This problem uses 6,478 binary variables in total and is solved using around
25s of QPU access time.
