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MRP Lot Sizing Rules: Which One Fits (Reference Table)

Choosing the wrong lot sizing rule creates either too many small orders or too much stock. This table summarises the common rules so a planner can pick one by item behaviour rather than by habit.

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Lot sizing rule	Also called	How it sizes an order	Best fit	Watch out for
Lot for lot	L4L, discrete, as required	Order equals the net requirement of each bucket	Expensive, high-value, make-to-order or low-volume items	Many small orders where setup or order cost is high
Fixed order quantity	FOQ, fixed lot size	Always the same quantity, repeated until the shortage is covered	Items with a natural batch, container or tooling size	Surplus when the requirement is much smaller than the lot
Economic order quantity	EOQ, Wilson formula	Quantity from sqrt(2 x annual demand x order cost / holding cost per unit)	Steady, independent demand with stable cost data	Assumes constant demand, which dependent demand rarely is
Periodic order quantity	POQ, period order quantity	Covers the net requirements of a fixed number of buckets in one order	Dependent demand where an order interval is easier than a quantity	Interval must be reviewed when demand changes level
Fixed period requirements	Fixed period, weekly or monthly grouping	Groups all requirements within a calendar period into one order	Suppliers who ship weekly, or monthly buying cycles	Early arrival of later requirements raises stock
Min-max or reorder level	Order-up-to, replenish to max	When stock falls to the minimum or reorder level, order up to the maximum	Low-value consumables, indirect materials, bin replenishment	Reactive to stock, not driven by BOM demand
Minimum order quantity	MOQ, minimum lot size	Order is at least the minimum, otherwise the net requirement	Vendors with a minimum purchase quantity	Often combined with a rounding multiple
Maximum order quantity	Maximum lot size	Caps order size and splits larger needs into several orders	Capacity, tank, oven or machine batch limits	May create several orders on the same day
Rounding multiple	Order multiple, rounding value	Rounds the order up to a multiple of a unit such as a pallet	Packaged goods, pallets, bar stock lengths	Rounding adds surplus on small requirements
Part period balancing	PPB, part-period algorithm	Combines future buckets while holding cost stays near the setup cost	Lumpy dependent demand with known setup and holding cost	Needs reliable cost data and recalculation when costs change
Least unit cost	LUC	Extends the order while cost per unit keeps falling	Items where setup and holding cost are known	Can overshoot the true optimum
Least total cost	LTC	Chooses the number of buckets where holding cost is closest to setup cost	Similar to part period balancing	Heuristic, not guaranteed optimal
Silver-Meal heuristic	Least period cost	Extends the order while average cost per period keeps falling	Time-varying demand where simplicity matters	Heuristic, may stop early if demand has later peaks
Wagner-Whitin	Dynamic programming lot sizing	Finds the lowest total setup plus holding cost over the whole horizon	Small number of high-value items with stable cost inputs	More computation, and small demand changes can reshuffle the plan

Cost-based rules need setup and holding cost inputs. Many ERPs only offer a subset, so check which rules your system supports before choosing.

Lot size review from your data

Optional: a read-only review of order sizes against recent demand history in your ERP.

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How to choose a rule

Start with the cost of an order against the cost of holding stock. If setup or order cost is tiny, lot for lot is usually right. If a vendor or process imposes a fixed batch or multiple, use fixed quantity with rounding. For steady items with stable cost data, EOQ or a periodic interval works. For lumpy demand with real setup cost, use periodic or a cost-balancing heuristic. Search by your item type in the table to see the closest match.

Quantity rules versus interval rules

Quantity rules such as fixed and EOQ decide how much to order. Interval rules such as periodic and fixed period decide how many buckets of demand one order covers. Interval rules follow dependent demand better because the order quantity floats with the requirement. Limits such as minimum, maximum and rounding can be layered on top of either family.

Common mistakes

Planners often copy one rule across a whole item class without checking cost data.

Using EOQ on lumpy dependent demand.
Setting a fixed lot far larger than the typical requirement.
Forgetting that a rounding multiple adds surplus.
Leaving cost-based rules on after setup costs changed.
Never reviewing the rule when demand level shifts.

Frequently Asked Questions

What is the simplest lot sizing rule?

Lot for lot is the simplest: each order equals the net requirement of one bucket. It keeps inventory minimal but creates the most orders, so it suits items with low setup or order cost, or items that are expensive to hold.

When is EOQ a poor choice?

EOQ assumes constant independent demand. For components whose demand comes from lumpy parent orders it can create stock that sits for months. Periodic or cost-balancing rules usually serve those items better.

Can I combine rules?

Yes. A base rule such as lot for lot or periodic is often combined with a minimum quantity, a maximum quantity and a rounding multiple. Many ERPs expose these as separate fields on the item planning data.

How often should lot sizes be reviewed?

Review when demand level, setup cost, supplier terms or holding cost change materially, and as a routine at least once or twice a year for high-value items. Stale lot sizes are a frequent hidden source of excess inventory.

If you want lot sizing suggestions tested against your real demand history, we can discuss running that analysis read-only on your ERP data.

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