  We present a Large Neighbourhood Search based approach for solving complex
long-term open-pit mine planning problems. An initial feasible solution,
generated by a sliding windows heuristic, is improved through repeated solves
of a restricted mixed integer program. Each iteration leaves only a subset of
the variables in our planning model free to take on new values. We form these
subsets through the use of a novel path-based neighbourhood structure, and
neighbourhood formation strategies that exploit the structure of the planning
model. We show that our method is able to find near-optimal solutions to
problems that cannot be solved by an off-the-shelf solver in a reasonable time,
or with reasonable computational resources.
