Cutlist Optimizer Editorial Team · Updated
Cutting List Optimization
Learn how cutting list optimization actually works — then run it: the optimizer below applies every technique on this page to your parts list.
Layout strategies per run
16
Part instances supported
1,000
Calculation precision
0.01 mm
Stock sheet
Parts to cut
9 parts in the list
| Part | Width (mm) | Height (mm) | Qty | Can rotate | |
|---|---|---|---|---|---|
Cut settings
Material your saw blade removes per cut
Keep-out distance from every sheet edge
Allow rotating parts
Everything runs in your browser — your cut list is never uploaded.
No results yet
Add your parts above and run the optimizer to see the layout, sheet count, efficiency and waste.
Cutting list optimization is the process of arranging every part of a project on stock material so that sheets, boards and panels are consumed as efficiently as possible. It sits between your cut list and your saw: the list says what to cut, optimization decides where. Done well, cutting list optimization is the cheapest material discount you will ever find — the same project, the same boards, simply planned better.
This page pairs a working optimizer with a plain-language guide to the method underneath it. You will see where utilization percentages come from, what kerf really costs, when rotation helps, and how a cutting list optimization engine chooses between candidate layouts. Then type your own parts above and watch the theory produce numbers.
The four inputs of cutting list optimization
Every cutting list optimization problem, from a two-shelf bookcase to a thousand-part commercial fit-out, is built from the same four inputs. Stock sheets define the container: width, height and how many you are willing to open. Parts define the cargo: label, width, height and quantity. Kerf defines the price of every cut — the slot of material the blade converts to sawdust. Constraints define what is allowed: rotation on or off, edge margins, grain rules.
Feed those four inputs to the optimizer above and it returns placements: an x/y position on a specific sheet for every part instance, plus the metrics that matter — sheets used, material utilization and waste percentage. The cutting list optimization engine tries multiple strategies because no single rule wins every job; it keeps whichever plan opens the fewest sheets.
Stock sheets: the container
Metric shops buy 2440 × 1220 mm sheet goods; imperial yards buy 4 × 8 ft. Both presets are one click away. Sheet quantity matters as much as size: a cutting list optimization run that knows you only have five sheets will tell you the moment the sixth would be needed, instead of silently planning material you do not own.
Parts: the cargo
Enter parts as finished sizes and let the optimizer handle arrangement. Quantity fields expand one row into many instances — four shelves is one row, not four. Labels flow through to the diagrams and the cut list, so the optimized plan reads like your project, not like abstract rectangles. Cutting list optimization only works when the parts list is honest, and honest lists are labeled lists.
Constraints: where cutting list optimization earns its keep
Kerf, rotation and margin are where cutting list optimization stops being arithmetic and starts being workshop-aware. Every constraint you set is honored on every placement, every run — which is the difference between an optimized plan and an optimistic one.
How the nesting engine decides
Under the hood, cutting list optimization uses bin-packing algorithms. This tool implements MaxRects: each sheet tracks a list of maximal free rectangles, and every part placement splits the rectangle it occupies into new free areas. Four heuristics score candidate positions — best short side fit, best long side fit, best area fit and bottom-left — because each excels on different part mixes. Combined with four part orderings, the engine evaluates sixteen complete plans per job and keeps the best.
The tie-break logic is deliberately conservative: fewer sheets always wins, and only equal sheet counts are compared on wasted area. That mirrors how a buyer thinks — a second sheet bought is a real cost, while five percent more offcut is an inconvenience.
Utilization, kerf and the real numbers
Material utilization is simply part area divided by sheet area, expressed as a percentage. A first pass with unsorted parts typically lands near 70–75%; the same list after cutting list optimization usually reaches 82–90%, with rotation pushing the top end. Kerf quietly eats into that: on a sheet holding forty cuts, a 3 mm blade removes a 122 mm strip of usable material — a full shelf's worth of area.
Waste percentage is the complement of utilization, but not all waste is equal. A single large offcut is storeroom inventory; ten scattered slivers are firewood. The SVG diagrams let you judge layout quality by eye: cutting list optimization that concentrates leftovers into usable rectangles is worth more than a slightly higher number that shatters the sheet.
Cutting list optimization in practice: a worked example
Take a small cabinet run on 2440 × 1220 mm plywood: two sides at 800 × 600, three panels at 720 × 450, four shelves at 400 × 300, kerf 3 mm. Press Load Example above to enter exactly this list. Without optimization, most people crosscut two sheets and fill a third; the engine nests everything on one sheet at roughly 81% utilization — visible proof that cutting list optimization pays for the saw blades.
Now edit the example: raise the shelf quantity to eight, or add a 2200 × 300 countertop. Watch how the optimizer opens sheets in sequence, places the long part first, and reports efficiency shifting — a live demonstration of every concept on this page.
Limits of the method — and how to plan around them
Cutting list optimization arranges rectangles; it cannot read grain through a veneer or know that a door must bookmatch its neighbor. Encode such rules yourself by switching rotation off for grain-critical parts. It also plans single-depth stacks: parts thicker than the sheet belong to a separate run. And remember that trimming allowance is yours to add — enter parts 2 mm oversize if you plane after cutting, and the optimizer will still place them honestly. Used within those limits, cutting list optimization is arithmetic, not opinion: the layout you print is the layout you get.
Frequently asked questions
What is cutting list optimization?
Cutting list optimization is the systematic arrangement of project parts onto stock sheets to minimize sheets used and waste generated, while respecting kerf, rotation and margin constraints. This page provides a free optimizer plus a full explanation of the cutting list optimization method.
How much material does optimization actually save?
Typical manual layouts sit at 70–75% utilization. The same lists usually reach 82–90% after cutting list optimization, which on a ten-sheet order means one to two sheets saved — every time the list is cut.
Does the optimizer consider blade kerf?
Yes. Every part is expanded by the kerf value during placement, so no two parts are ever closer than one blade width. Kerf area is included in the utilization math — cutting list optimization without kerf is just drawing.
Should I always allow rotation?
Allow it for utility parts, forbid it for grain-critical pieces. Rotation typically adds several points of utilization, but only your project knows which parts may turn.
What does the efficiency percentage mean?
It is total part area divided by total sheet area of the sheets the plan opened. Ninety percent means only a tenth of the purchased material ends up as offcut.
Can I use the optimizer for MDF, particleboard or acrylic?
Yes — the engine is material-agnostic. Sheet size, kerf and rotation are the only material-dependent inputs, so the same cutting list optimization workflow covers plywood, MDF, melamine, foam board and acrylic.
Is there a limit on parts?
Up to 1,000 part instances per run, computed in a background worker so the page stays responsive even on large lists.
How do I print the optimized layout?
Run the optimizer, then press Print. The printed page contains only the sheet diagrams and cut list — no navigation or marketing text.
References & sources
“Cutting and packing problems ask how large objects are cut into smaller pieces so that demand is met and the consumption of material — or waste — is minimized.”
— Dyckhoff, H. (1990), A Typology of Cutting and Packing Problems
- Jylänki, J. (2010). A Thousand Ways to Pack the Bin — A Practical Approach to Two-Dimensional Rectangle Bin Packing. — MaxRects heuristics used by this nesting engine.
- Burke, E. K., Kendall, G. & Whitwell, G. (2004). A New Placement Heuristic for the Orthogonal Stock-Cutting Problem. Operations Research, 52(4). — bottom-left placement for sheet cutting.
- Dyckhoff, H. (1990). A Typology of Cutting and Packing Problems. European Journal of Operational Research, 44(2), 145–159. — the standard classification of cutting problems.
Related cutting tools
Every tool runs locally in your browser and shares the same sheet-cutting engine.