ILP-Based Scheduling Optimization for MMX Landing Site Observations With Operation Constraints

Phobos observations for MMX landing-site selection (LSS) present a complex combinatorial optimization problem: maximizing the number of observations while satisfying stringent mission requirements. In our previous work, we addressed this problem using a genetic algorithm (GA), which is well suited to nonlinear problems. However, for the MMX mission, the mission requirements are such that the constraints can be linearized without approximations, making Integer Linear Programming (ILP) particularly effective[1]. ILP yields optimal results and can directly express strong constraints, such as resource limitations. This paper presents an ILP formulation of the LSS observation scheduling problem that incorporates detailed mission constraints corresponding to the generation of a local shape model of Phobos. The simulation results demonstrate the effectiveness of the ILP-based optimization compared to GA in the context of the MMX mission requirements.