Regional Constellation Reconfiguration Problem: Integer Linear Programming Formulation and Lagrangian Heuristic Method

A group of satellites, with either homogeneous or heterogeneous orbital characteristics and/or hardware specifications, can undertake a reconfiguration process due to variations in operations pertaining Earth observation missions. This paper investigates the problem optimizing satellite constellation against two competing mission objectives: 1) maximization total coverage reward, and 2) minimization cost transfer. The decision variables for include design new configuration assignment satellites from one another. We present novel biobjective integer linear programming formulation that combines transfer problems. lends itself use generic mixed-integer (MILP) methods such as branch-and-bound algorithm computation provably optimal solutions; however, these approaches become computationally prohibitive even moderately sized instances. In response this challenge, proposes Lagrangian relaxation-based heuristic method leverages structure embedded problem. results computational experiments attest near-optimality solutions significant improvement runtime compared commercial MILP solver.