A Time-Dependent TSP Formulation for the Design of an Active Debris Removal Mission using Simulated Annealing
This addresses mission planning for space debris cleanup, but it is incremental as it applies known methods to a specific domain.
The paper tackled the Active Debris Removal Mission Design problem by formulating it as a Time-Dependent Traveling Salesman Problem and solving it with a Simulated Annealing algorithm, achieving optimization for up to 20 targets.
This paper proposes a formulation of the Active Debris Removal (ADR) Mission Design problem as a modified Time-Dependent Traveling Salesman Problem (TDTSP). The TDTSP is a well-known combinatorial optimization problem, whose solution is the cheapest mono-cyclic tour connecting a number of non-stationary cities in a map. The problem is tackled with an optimization procedure based on Simulated Annealing, that efficiently exploits a natural encoding and a careful choice of mutation operators. The developed algorithm is used to simultaneously optimize the targets sequence and the rendezvous epochs of an impulsive ADR mission. Numerical results are presented for sets comprising up to 20 targets.