Economic Order Quantity

EOQ · HARRIS (1913)

Logistics · Inventory · Tactical

The Economic Order Quantity is the oldest closed-form result in operations research: given a constant demand rate $D$, a fixed cost $S$ per order, and a holding cost $h$ per unit per unit time, what order quantity $Q$ minimises the total annual cost of ordering plus holding? Ford Whitman Harris (1913) derived the square-root formula $Q^* = \sqrt{2DS/h}$ — arguably the first quantitative inventory result. R. H. Wilson (1934) popularised it, and it has been the starting point of every inventory-management textbook since. This page presents the derivation, the optimal formula, an interactive cost-curve visualiser, and the principal extensions (quantity discounts, backorders, EPQ).

Why EOQ matters

The first closed-form in OR

1913
Harris derives EOQ in the Factory trade magazine — a century before the software era. Still taught in every inventory management course.
Harris (1913); Erlenkotter (1990) historical note · doi:10.1287/opre.38.6.947
√(2DS/h)
The square-root formula — robust to mis-estimated parameters thanks to the flat total-cost curve near the optimum. A 2× error in $S$ or $h$ yields only a ~6% cost penalty.
Zipkin (2000), Ch. 3.
Cornerstone
EOQ is the base case — Wagner-Whitin generalises to time-varying demand; $(Q,r)$ and $(s,S)$ add stochastic demand; newsvendor trades perishability.
Axsäter (2015) Inventory Control.

Derivation & formula

From cost function to Q*

Assumptions

Classical EOQ assumes: constant deterministic demand $D$ (units/year); a fixed setup or ordering cost $S$ per order (independent of order size); a constant holding cost $h$ per unit per year; instantaneous replenishment; no stockouts; infinite horizon; no quantity discounts. Under these assumptions, an optimal policy orders a fixed quantity $Q$ whenever inventory reaches a reorder point (here, zero — zero lead time and no safety stock).

Notation

SymbolMeaning
$D$annual demand rate (units / year)
$S$fixed ordering / setup cost per order ($)
$h$holding cost per unit per year ($)
$Q$decision variable: quantity ordered per cycle
$TC(Q)$total annual cost as a function of $Q$

Total annual cost

Orders per year $= D/Q$, so annual ordering cost is $S \cdot D/Q$. Average on-hand inventory between replenishments is $Q/2$, so annual holding cost is $h \cdot Q/2$. Ignoring the (constant) purchase cost:

Total cost function
$$TC(Q) = \frac{D}{Q}\,S + \frac{Q}{2}\,h$$

Optimal order quantity

$TC(Q)$ is convex; the first-order condition $dTC/dQ = 0$ gives:

Harris-Wilson formula
$$Q^* \;=\; \sqrt{\frac{2DS}{h}}$$
Optimal total cost
$$TC(Q^*) \;=\; \sqrt{2DSh}$$

Robustness near the optimum

The cost function is remarkably flat near $Q^*$: ordering $1.5 Q^*$ or $0.67 Q^*$ only raises total cost by ~8%. This is why EOQ survives real-world mis-estimation of $S$ and $h$.

Principal extensions

  • Economic Production Quantity (EPQ) — finite production rate $P > D$: $Q^* = \sqrt{2DS / (h (1 - D/P))}$.
  • EOQ with planned backorders — shortage cost $b$ per unit-year: $Q^* = \sqrt{2DS/h} \cdot \sqrt{(h+b)/b}$ with optimal stockout fraction $b/(h+b)$.
  • Quantity discounts — piecewise-constant unit price; evaluate $TC$ at each discount break and at the in-interval $Q^*$.
  • Stochastic demand — $(Q, r)$ continuous-review and $(s, S)$ periodic-review policies (Arrow-Harris-Marschak 1951; Scarf 1960).
  • Time-varying demand — Wagner & Whitin (1958) dynamic-programming lot sizing.

Interactive calculator

Slide $D$, $S$, $h$ · watch $Q^*$ and the cost curve update

Demand D (units / yr)
2000
Ordering cost S ($)
100
Holding cost h ($/unit-yr)
5.0
Q* (optimal)
Orders / yr
Cycle length (days)
TC(Q*) ($/yr)

Key references

DOIs & permanent URLs

Harris, F. W. (1913).
“How many parts to make at once.”
Factory, The Magazine of Management, 10(2), 135–136. Reprinted Operations Research 38(6), 1990, 947–950. doi:10.1287/opre.38.6.947
Wilson, R. H. (1934).
“A scientific routine for stock control.”
Harvard Business Review, 13, 116–128.
Erlenkotter, D. (1990).
“Ford Whitman Harris and the economic order quantity model.”
Operations Research, 38(6), 937–946. doi:10.1287/opre.38.6.937
Arrow, K. J., Harris, T., & Marschak, J. (1951).
“Optimal inventory policy.”
Econometrica, 19(3), 250–272. doi:10.2307/1906813
Scarf, H. (1960).
“The optimality of (s,S) policies in the dynamic inventory problem.”
In Mathematical Methods in the Social Sciences, Arrow et al. (eds.), Stanford University Press.
Wagner, H. M., & Whitin, T. M. (1958).
“Dynamic version of the economic lot size model.”
Management Science, 5(1), 89–96. doi:10.1287/mnsc.5.1.89
Zipkin, P. H. (2000).
Foundations of Inventory Management.
McGraw-Hill.
Axsäter, S. (2015).
Inventory Control (3rd ed.).
Silver, E. A., Pyke, D. F., & Thomas, D. J. (2016).
Inventory and Production Management in Supply Chains (4th ed.).

Rebuilding an inventory policy?
EOQ is the anchor; let's find the right extension for your setting.

Get in Touch
Data and numerical examples are illustrative. Pages on this site are educational tools, not production software.