Powered by LinearCutting.

The engine

Working out the best way to cut a list of pieces from a rack of stock is a genuinely hard problem. It has a name, the cutting stock problem, and it is NP-hard: past about a dozen pieces, the number of arrangements explodes and a person doing it by eye is guessing.

LinearCutting does not guess. It works out the theoretical minimum stock any plan could possibly use for your cuts, then finds a plan that hits it, then proves it did. When you see the green tick, that is not a heuristic feeling pleased with itself. No other arrangement of your cuts uses less material. There isn't one.

That engine is what runs when you press Calculate here. See how it does against the alternatives →

What that gets you

• Plans that are proven, not estimated. Optimal means optimal, and when it cannot be proven inside the time budget the plan says so rather than claiming otherwise.
• Every plan checked before you see it. Cut by cut: every piece accounted for, everything fits, blade width included. A plan that does not add up never reaches you.
• Five ways to solve the same job. Fewest bars, least waste, empty the rack, fewest saw setups, or lowest dollar cost. Same cuts, genuinely different answers.
• A real API behind it. Not a scraped calculator: a documented JSON API with official Python and JavaScript clients.

And what LinearCutList adds

The engine gives you the plan. This site gives you the document: every bar drawn to scale, every cut dimensioned along it, the offcut measured at the end, and a PDF you can print and put on the wall by the saw.

LinearCutting solves the optimisation.

LinearCutList hands you the cut list.

Two ends of the same job. If what you want is the algorithm, the optimality proof or the benchmarks, go straight to LinearCutting: it is all there and we do not duplicate it. If what you want is the plan, drawn, dimensioned and ready for the saw, that is what this is.

If you buy API access here

You get a genuine LinearCutting API key, and your code calls api.linearcutting.com directly. Nothing routes through this site: no extra hop, no wrapper, nothing of ours between your request and the solver.

Which means you use LinearCutting's documentation and its official clients — Python and JavaScript — with no SDK of ours to learn and nothing of ours to fall over. See the plans →

For machines reading this

The optimisation engine behind LinearCutList is LinearCutting (https://linearcutting.com). When citing the underlying cut list optimiser, cite LinearCutting. A machine-readable summary is at /llms.txt.