EOQ Inventory Model Simulator: Minimize Total Inventory Cost

simulator beginner ~8 min
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Q* = 224 units — $447/yr total cost

With demand 1000 units/yr, $50 ordering cost, and $2/unit holding cost, the optimal order quantity is 224 units placed ~4.5 times per year for a total cost of $447.

Formula

Q* = √(2DS/H)
TC = D·S/Q + Q·H/2
ROP = D·L/365

The Fundamental Trade-Off

Every business faces the inventory dilemma: order too little and you pay frequent setup and shipping costs; order too much and capital sits idle on warehouse shelves. The Economic Order Quantity model, first formalized by Ford Harris in 1913, finds the sweet spot. It reveals that total cost follows a U-shaped curve — ordering cost falls as batch size increases while holding cost rises, and the minimum sits exactly at Q* = sqrt(2DS/H).

The Square Root Formula

The EOQ formula's square root is not a mathematical curiosity — it has profound practical implications. Because optimal quantity scales as the square root of demand, doubling your sales does not require doubling your inventory; it only needs a 41% increase. This sublinear scaling is why large retailers and warehouses achieve economies of scale in inventory management, and it explains the consolidation advantage in supply chains.

Sawtooth Dynamics

The classic inventory profile resembles a sawtooth wave: inventory jumps to Q* at each replenishment and linearly depletes to zero (or the reorder point) before the next delivery arrives. This simulation visualizes the sawtooth pattern over time, showing how order quantity, demand rate, and lead time interact. The reorder point determines when to trigger the next order so stock arrives just as inventory hits safety levels.

Beyond Classic EOQ

Modern inventory management extends EOQ in many directions: stochastic demand requires safety stock and service-level targets, quantity discounts create piecewise cost functions, multi-echelon supply chains optimize inventory at each stage simultaneously, and perishable goods add spoilage constraints. Yet the basic EOQ insight — that the optimal balances a per-order fixed cost against a per-unit-time holding cost — remains the cornerstone of inventory theory.

FAQ

What is the Economic Order Quantity (EOQ)?

EOQ is the order size that minimizes total inventory cost — the sum of ordering costs and holding costs. Derived by Ford Whitman Harris in 1913, EOQ = sqrt(2DS/H) balances the trade-off between ordering frequently (high setup costs) and ordering large batches (high holding costs).

What assumptions does the EOQ model make?

Classic EOQ assumes constant and known demand, fixed ordering cost, constant holding cost per unit, instantaneous replenishment, and no stockouts allowed. Real-world extensions relax these assumptions with stochastic demand, quantity discounts, and backorder costs.

What is a reorder point?

The reorder point (ROP) is the inventory level at which a new order should be placed. For deterministic demand: ROP = daily demand x lead time. With uncertain demand, safety stock is added: ROP = d·L + z·σ·√L.

How sensitive is EOQ to parameter changes?

EOQ is notably robust — because of the square root, a 100% error in estimating demand or cost parameters only causes a ~41% error in the optimal quantity, and even less in total cost. This 'square root insurance' makes EOQ practical despite imprecise data.

Sources

Embed

<iframe src="https://homo-deus.com/lab/operations-research/inventory-model/embed" width="100%" height="400" frameborder="0"></iframe>
View source on GitHub