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Economic Order Quantity (EOQ), also known as Economic Buying Quantity (EPQ), is the order quantity that minimizes the total
holding cost In marketing, carrying cost, carrying cost of inventory or holding cost refers to the total cost of holding inventory. This includes warehousing costs such as rent, utilities and salaries, financial costs such as opportunity cost, and inventory co ...
s and ordering costs in inventory management. It is one of the oldest classical
production scheduling Scheduling is the process of arranging, controlling and optimizing work and workloads in a Production (economics), production process or manufacturing process. Scheduling is used to allocate plant and machinery resources, plan human resources, plan ...
models. The model was developed by Ford W. Harris in 1913, but R. H. Wilson, a consultant who applied it extensively, and K. Andler are given credit for their in-depth analysis.


Overview

EOQ applies only when
demand In economics, demand is the quantity of a good that consumers are willing and able to purchase at various prices during a given time. The relationship between price and quantity demand is also called the demand curve. Demand for a specific item ...
for a product is constant over the year and each new order is delivered in full when inventory reaches zero. There is a fixed cost for each order placed, regardless of the number of units ordered; an order is assumed to contain only 1 unit. There is also a cost for each unit held in storage, commonly known as
holding cost In marketing, carrying cost, carrying cost of inventory or holding cost refers to the total cost of holding inventory. This includes warehousing costs such as rent, utilities and salaries, financial costs such as opportunity cost, and inventory co ...
, sometimes expressed as a percentage of the purchase cost of the item. While the EOQ formulation is straightforward there are factors such as transportation rates and quantity discounts to consider in actual application. We want to determine the optimal number of units to order so that we minimize the total cost associated with the purchase, delivery, and storage of the product. The required parameters to the solution are the total demand for the year, the purchase cost for each item, the fixed cost to place the order for a single item and the storage cost for each item per year. Note that the number of times an order is placed will also affect the total cost, though this number can be determined from the other parameters.


Variables

*T = total annual inventory cost *P = purchase unit price, unit production cost *Q = order quantity *Q^* = optimal order quantity *D = annual demand quantity *K = fixed cost per order, setup cost (''not'' per unit, typically cost of ordering and shipping and handling. This is not the cost of goods) *h = annual holding cost per unit, also known as carrying cost or storage cost (capital cost, warehouse space, refrigeration, insurance, opportunity cost (price x interest), etc. usually not related to the unit production cost)


The total cost function and derivation of EOQ formula

The single-item EOQ formula finds the minimum point of the following cost function: Total Cost = purchase cost or production cost + ordering cost + holding cost Where: * Purchase cost: This is the variable cost of goods: purchase unit price × annual demand quantity. This is P × D * Ordering cost: This is the cost of placing orders: each order has a fixed cost K, and we need to order D/Q times per year. This is K × D/Q * Holding cost: the average quantity in stock (between fully replenished and empty) is Q/2, so this cost is h × Q/2 : T = PD + K + h . To determine the minimum point of the total cost curve, calculate the
derivative In mathematics, the derivative of a function of a real variable measures the sensitivity to change of the function value (output value) with respect to a change in its argument (input value). Derivatives are a fundamental tool of calculus. ...
of the total cost with respect to Q (assume all other variables are constant) and set it equal to 0: : = -+ Solving for Q gives Q* (the optimal order quantity): : Q^= Therefore: Q* is independent of P; it is a function of only K, D, h. The optimal value Q* may also be found by recognizing that : T = + + PD =(Q - \sqrt)^2 + \sqrt +PD, where the non-negative quadratic term disappears for Q = \sqrt, which provides the cost minimum T_ = \sqrt + PD.


Example

*annual requirement quantity (D) = 10000 units *Cost per order (K) = 40 *Cost per unit (P)= 50 *Yearly carrying cost per unit = 4 *Market interest = 2% Economic order quantity = \sqrt = \sqrt = \sqrt = 400 units Number of orders per year (based on EOQ) = = 25 Total cost = P\cdot D + K (D/EOQ) + h (EOQ/2) Total cost = 50\cdot 10000 + 40\cdot (10000/400) + 5\cdot (400/2) = 502000 If we check the total cost for any order quantity other than 400(=EOQ), we will see that the cost is higher. For instance, supposing 500 units per order, then Total cost = 50\cdot 10000 + 40\cdot (10000/500) + 5\cdot (500/2) = 502050 Similarly, if we choose 300 for the order quantity, then Total cost = 50\cdot 10000 + 40\cdot (10000/300) + 5\cdot (300/2) = 502083.33 This illustrates that the economic order quantity is always in the best interests of the firm.


Extensions of the EOQ model


Quantity discounts

An important extension to the EOQ model is to accommodate quantity discounts. There are two main types of quantity discounts: (1) all-units and (2) incremental. Here is a numerical example: * Incremental unit discount: Units 1–100 cost $30 each; Units 101–199 cost $28 each; Units 200 and up cost $26 each. So when 150 units are ordered, the total cost is $30*100 + $28*50. * All units discount: an order of 1–1000 units costs $50 each; an order of 1001–5000 units costs $45 each; an order of more than 5000 units costs $40 each. So when 1500 units are ordered, the total cost is $45*1500. In order to find the optimal order quantity under different quantity discount schemes, one should use algorithms; these algorithms are developed under the assumption that the EOQ policy is still optimal with quantity discounts. Perera et al. (2017) establish this optimality and fully characterize the (s,S) optimality within the EOQ setting under general cost structures.


Design of optimal quantity discount schedules

In presence of a strategic customer, who responds optimally to discount schedules, the design of an optimal quantity discount scheme by the supplier is complex and has to be done carefully. This is particularly so when the demand at the customer is itself uncertain. An interesting effect called the "reverse bullwhip" takes place where an increase in consumer demand uncertainty actually reduces order quantity uncertainty at the supplier.


Backordering costs and multiple items

Several extensions can be made to the EOQ model, including backordering costs and multiple items. In the case backorders are permitted, the inventory carrying costs per cycle are: : IC \int\limits_^(Q-s-\lambda t)\,dt = \frac (Q-s)^2, where s is the number of backorders when order quantity Q is delivered and \lambda is the rate of demand. The backorder cost per cycle is: : \pi s + \hat \int\limits_^\lambda t dt =\pi s +\frac \hat \lambda T^_ = \pi s + \frac, where \pi and \hat are backorder costs, T_=T-T_, T being the cycle length and T_=(Q-s) / \lambda. The average annual variable cost is the sum of order costs, holding inventory costs and backorder costs: : \mathcal = \frac A+\frac IC (Q-s)^2+\frac \pi \lambda s+ \frac \hat s^/math> To minimize \mathcal impose the
partial derivatives In mathematics, a partial derivative of a function of several variables is its derivative with respect to one of those variables, with the others held constant (as opposed to the total derivative, in which all variables are allowed to vary). Pa ...
equal to zero: : \frac =- \frac \left A+\frac IC (Q-s)^2+\pi \lambda s+ \frac \hat s^ \right\frac(Q-s)=0 : \frac =-\frac(Q-s) + \frac \pi \lambda + \frac \hat s =0 Substituting the second equation into the first gives the following
quadratic equation In algebra, a quadratic equation () is any equation that can be rearranged in standard form as ax^2 + bx + c = 0\,, where represents an unknown value, and , , and represent known numbers, where . (If and then the equation is linear, not qu ...
: : hat ^ + \hat ICs^2 +2\pi \hat \lambda s+(\pi \lambda) ^2 -2 \lambda A IC=0 If \hat=0 either s=0 or s=\infty is optimal. In the first case the optimal lot is given by the classic EOQ formula, in the second case an order is never placed and minimum yearly cost is given by \pi \lambda. If \pi > \sqrt =\delta or \pi \lambda > K_ s^*=0 is optimal, if \pi<\delta then there shouldn't be any inventory system. If \hat\ne0 solving the preceding quadratic equation yields: : s^* = hat + IC^ \left ( -\pi \lambda + \left (2\lambda AIC) \left ( 1 + \frac \right)- \frac(\pi \lambda )^ \right \right ) : Q^* = \left \frac \right \left \frac -\frac \right If there are backorders the reorder point is: r^*_ = \mu - mQ^* - s^*; with m being the largest integer m \leq \frac and μ the lead time demand. Additionally, th
economic order interval
can be determined from the EOQ and the economic production quantity model (which determines the optimal production quantity) can be determined in a similar fashion. A version of the model, the Baumol-Tobin model, has also been used to determine the
money demand In monetary economics, the demand for money is the desired holding of financial assets in the form of money: that is, cash or bank deposits rather than investments. It can refer to the demand for money narrowly defined as M1 (directly spendabl ...
function, where a person's holdings of money balances can be seen in a way parallel to a firm's holdings of inventory. Malakooti (2013) has introduced the multi-criteria EOQ models where the criteria could be minimizing the total cost, Order quantity (inventory), and Shortages. A version taking the time-value of money into account was developed by Trippi and Lewin.


Imperfect quality

Another important extension of the EOQ model is to consider items with imperfect quality. Salameh and Jaber (2000) are the first to study the imperfect items in an EOQ model very thoroughly. They consider an inventory problem in which the demand is deterministic and there is a fraction of imperfect items in the lot and are screened by the buyer and sold by them at the end of the circle at discount price.


See also

* Reorder point *
Safety stock Safety stock is a term used by logisticians to describe a level of extra stock that is maintained to mitigate risk of stockouts (shortfall in raw material or packaging) caused by uncertainties in supply and demand. Adequate safety stock levels pe ...
* Constant fill rate for the part being produced: Economic production quantity * Orders placed at regular intervals: Fixed time period model * Demand is random: classical Newsvendor model * Demand varies over time: Dynamic lot size model * Several products produced on the same machine: Economic lot scheduling problem * Renewal Demand and (s, S) Optimality by Perera, Janakiraman, and Ni


References


Further reading

* Harris, Ford W. ''Operations Cost'' (Factory Management Series), Chicago: Shaw (1915) * * Camp, W. E. "Determining the production order quantity", Management Engineering, 1922 * * Plossel, George. Orlicky's Material Requirement's Planning. Second Edition. McGraw Hill. 1984. (first edition 1975) * * * * Tsan-Ming Choi (Ed.) Handbook of EOQ Inventory Problems: Stochastic and Deterministic Models and Applications, Springer's International Series in Operations Research and Management Science, 2014. . *


External links


The EOQ Model
* http://www.inventoryops.com/economic_order_quantity.htm *http://www.scmfocus.com/supplyplanning/2014/04/10/economic-order-quantity-calculator/ {{DEFAULTSORT:Economic Order Quantity Inventory optimization de:Klassische Losformel