Executable by design: the MineLib McLaughlin benchmark

MineLib is a public library of open pit mining problems, set up as the mining equivalent of MIPLIB and used as a common reference set across the field. It is published at minelib.org and described in Espinoza, Goycoolea, Moreno and Newman, "MineLib: a library of open pit mining problems", Annals of Operations Research 206(1), 2013.

We took McLaughlin, a defunct gold mine in California and the largest instance in the library at 2,140,342 blocks, together with the best-known published solution for it. That solution is a strong one. MineLib records its gap to the linear programming upper bound at 0.2%, so against the model it was given it is close to the best answer available.

The instance economics are the library's own and unchanged: gold at $900 per ounce, mining cost $1.32 per ton, processing cost $19 per ton, 90% recovery, and a 15% discount rate.

The model those economics sit in is the issue. The published problem schedules every block individually with no fleet, no haulage, no drill-and-blast timing and no capital model at all.

Around 60% of the stated value does not survive. The largest single cause is timing. Roughly 95% of the published schedule's first-period mill feed cannot physically be reached that early, principally because drill-and-blast preparation takes time, and partly because a limited number of dig faces can only strip so much material at once. That feed moves later, and discounting erodes it.

This is not a criticism of the solution or of the people who produced it. It answers the model it was handed extremely well. The model simply does not describe a mine.

The Cognomine plan carries $312,544,025 more NPV, at 151.8% of the practicalised comparator, on a plan that satisfies every constraint listed above.

The undiscounted line points the other way, and the reason matters. The published schedule moves around 2.6 times more total material and processes roughly 17% more ore, so its undiscounted total is higher. It over-selects, because nothing in its model told it that reaching material takes time and equipment. The Cognomine plan is more selective and better sequenced, and holds far more of its value once time is priced in.

Every mine plan leaves ore in the ground. Deciding what is worth extracting and what is not is one of the central judgements in a strategic plan, and both plans here make it. The difference is what informs the decision.

Both plans compute the cutoff as they go rather than taking a fixed grade, and both work from the same raw block data. The difference is what the calculation can see. Cognomine prices the fleet, haulage and drill-and-blast time needed to reach a block, so material that costs more to reach than it returns is left in place. The published formulation has no way to represent those costs, so its cutoff is computed as though reaching a block were free. That is why it moves more rock and processes more ore for less value.

Both plans above are solved to maximise net present value. Recovery, production rate, cost profile and capital sequencing can each be set as the objective instead, and a plan built to maximise recovery would mine more of this deposit and return a lower NPV. Which of those a site wants is a commercial decision, not a solver setting we make on its behalf.

A plan is only worth what a site can execute. The value lost between the two figures above is why experienced planners discount optimisation output before they read it, and they are right to.

Cognomine models the constraints that shape a real mine plan from the start, so the number it produces is a number the operation can work towards.