Coordinating the mobile production fleet in underground mines becomes increasingly important as the machines are more and more automated. We present a scheduling approach that applies to several of the most important production methods used in underground mines. Our algorithm combines constraint programming with a large neighborhood search strategy that dynamically adjusts the neighborhood size. The resulting algorithm is complete and able to rapidly improve constructed schedules in practice. In addition, it has important benefits when it comes to the acceptance of the approach in real-life operations. Our approach is evaluated on public and private industrial problem instances representing different mines and production methods. We find significant improvements over the current industrial practice.