Monte-Carlo Tree Search in Dragline Operation Planning

Abstract

Draglines are one of the largest earthmoving machines in surface mining. They are employed to remove the overburden near the surface, giving access to a seam of the target mineral or coal underneath. Their excavation productivity is significantly affected by the high-level operation strategy of where to position the dragline, what to dig at each position and where to dump the removed material. This letter explores the potential of using the Monte-Carlo tree search (MCTS) algorithm for planning this operation strategy. To this end, we adapt the MCTS algorithm to compute the dragline positioning sequences when a fixed digging and dumping strategy is applied at each position. The performance of the adapted MCTS algorithm is compared to a previously developed A* search algorithm and a greedy algorithm. Simulation results show that the MCTS algorithm is able to find near-optimal positioning sequences using significantly less time and memory than the A* algorithm. The solutions from the MCTS algorithm also largely outperform the solutions from the greedy algorithm in all the test scenarios. These results suggest that the MCTS algorithm can be used to plan the operation strategy when decisions about the digging and dumping operations are also considered.