Multi-Objective Evolutionary Algorithms for Scheduling the James Webb Space Telescope

Effective scheduling of the James Webb Space Telescope (JWST) requires managing the trade-off between multiple scheduling criteria including minimizing unscheduled time, angular momentum build-up, and the number of observations that miss their last opportunity to schedule. Previous studies examined momentum management and wasted space and showed that effective JWST scheduling requires modeling momentum as a resource that is three-dimensional, where activities can either produce or consume resources depending on when they are scheduled. We enrich the scheduling model by adding the ability to schedule JWST at different spacecraft roll angles and show that this ability has a strong impact on managing momentum. A series of multi-objective evolutionary algorithms are developed which incorporate different techniques to search the enriched domain. The algorithms are empirically evaluated showing that the best solutions are generated by the approach that evaluates the least number of candidate solutions.