EOQ vs Min/Max
Min/Max is a two-bin policy: when stock drops to Min (the reorder point), order up to Max. EOQ is the optimization that tells you how to set Max-minus-Min. They’re not really competitors - Min/Max with Max - Min = Q* is the continuous-review (s, Q) policy with Q set to Wilson’s value[1]. The real question is whether you bother to compute Q* or eyeball it.
The relationship, in one line
Set Min = ROP (lead-time demand plus safety stock). Set Max = Min + Q*. Reorder up to Max each time stock crosses Min. This is identical to running a continuous-review (s, Q) policy with Q = Q_Wilson, which is the optimal lot-sizing policy under constant demand.
The cost-flatness argument for eyeballing Max - Min
Wilson’s cost curve is flat near Q*: a 50 percent error in Q produces only about 6 percent excess total cost. So shops that eyeball Max - Min at a "round month of supply" rather than computing Q* exactly are usually within a few percent of optimal. That’s the genuine case for sticking with naive Min/Max: simplicity has a cost too.
When the gap stops being small
- S has changed a lot (new vendor, new freight contract) and the old eyeballed Max - Min is now off by 2x or more.
- Carrying cost percentage has shifted (interest rates moved, warehouse rent jumped) and you’re no longer near the historical Q*.
- The SKU is A-class (high $ volume) where a 6 percent cost gap is meaningful in dollars.
- You’re running thousands of SKUs and even small per-SKU savings aggregate.
The decision in one sentence
Use Min/Max as the operational mechanism, but compute Q* (Wilson) to set Max - Min. Eyeballing is fine for C-class items; compute for A-class.