On a stochastic extension of the EOQ formula

This note considers the classical EOQ model with finite replenishment rate, under stochastic lead time. It shows that if crossover of orders is prohibited and the model's parameters are such that the system experiences each cycle both positive stock and shortage the solution is closed form and is an intuitive extension of the EOQ formula.     

EOQ under Date-terms Supplier Credit

This paper examines EOQ under date-terms supplier credit, making explicit the separate effects on inventory policy of the two components of carrying cost-namely, financing cost and other variable holding costs. When a distinction between these types of holding costs is made, EOQ can no longer be expressed as a simple formula. Rather, optimal order quantity must be determined by search over a well-defined range of order quantities which encompasses the classical EOQ. The conclusion currently contained in the literature that the optimal order quantity under date terms is always given by an integer multiple of monthly demands no longer applies. In particular, a unique feature of date-terms credit is the possible existence of multiple EOQs.     

Using the complete squares method to analyze a lot size model when the quantity backordered and the quantity received are both uncertain

Several researchers have recently derived formulae for economic order quantities (EOQs) with some variants without reference to the use of derivatives, neither for first-order necessary conditions nor for second-order sufficient conditions. In addition, this algebraic derivation immediately produces an individual formula for evaluating the minimum expected annual cost. The purpose of this paper is threefold. First, this study extends the previous result to the EOQ formula, taking into account the scenario where the quantity backordered and the quantity received are both uncertain. Second, the complete squares method can readily derive global optimal expressions from a non-convex objective function in an algebraic manner. Third, the explicit identification of some analytic cases can be obtained: it is not as easy to do this using decomposition by projection. A numerical example has been solved to illustrate the solution procedure. Finally, some special cases can be deduced from the EOQ model under study, and concluding remarks are drawn.     

EOQ under Date-terms Supplier Credit: A Near-optimal Solution

This paper shows that under date-terms supplier credit, making explicit the separate effects of carrying cost, the financing and other marginal holding costs, does not invalidate Kingsman's original result that the optimal order quantity is given by an integer multiple of monthly demands, provided the capital investment component of the inventory holding costs is equal to or greater than 30% of the component due to the physical holding of inventory. The analysis is extended to the case when orders of less than a month's demand are optimal. Here it is shown that the order quantity should be an integer fraction of a month's demand, provided that the capital investment component of the inventory holding charge is equal to or greater than one quarter of the component due to the physical holding of inventory. It is argued that these conditions are likely to be satisfied for most if not all practical inventory situations. Combining these results with those of Carlson and Rousseau leads to a simple formula for the general optimal policy. The EOQ can still be expressed as a simple formula, so for practical situations generally there is no need to use the numerical search procedure these authors propose.     

Note: An application of the EOQ model with nonlinear holding cost to inventory management of perishables

In this note, we consider a variation of the economic order quantity (EOQ) model where cumulative holding cost is a nonlinear function of time. This problem has been studied by Weiss [Weiss, H., 1982. Economic order quantity models with nonlinear holding costs. European Journal of Operational Research 9, 56–60], and we here show how it is an approximation of the optimal order quantity for perishable goods, such as milk, and produce, sold in small to medium size grocery stores where there are delivery surcharges due to infrequent ordering, and managers frequently utilize markdowns to stabilize demand as the product’s expiration date nears. We show how the holding cost curve parameters can be estimated via a regression approach from the product’s usual holding cost (storage plus capital costs), lifetime, and markdown policy. We show in a numerical study that the model provides significant improvement in cost vis-à-vis the classic EOQ model, with a median improvement of 40%. This improvement is more significant for higher daily demand rate, lower holding cost, shorter lifetime, and a markdown policy with steeper discounts.     

Economic Order Quantities with Inflation

The classical EOQ formula assumes that all relevant costs and prices are constant. In this paper it is shown that with inflation the choice of the inventory carrying charge used in the EOQ formula depends on the company's pricing policy. If prices change independently of replenishment order timing the inventory charge should be low and independent of the inflation rate. However, when no "double ticketing" is permitted and the company uses a constant percentage mark up the carrying charge is high and depends on the inflation rate and the mark-up. Only if the company is allowed a fixed monetary margin is the classical result for carrying charge valid.     

An EOQ Model with Substitutions Between Products

In this paper, we present an economic order quantity (EOQ) model when two products are required, and one can be substituted for the other, if necessary, at a given unit cost. We consider three cases: (i) when there is no substitution between the products, (ii) when there is full substitution between the products, and (iii) when there is partial substitution between the products. In a deterministic setting with proportional substitution costs, we would expect to find full substitution or no substitution being optimal, depending on the cost parameters. However, we observe that full substitution is never optimal; only partial substitution or no substitution may be optimal. This result can best be explained due to the non-linearity of the decision variables in the total cost expression. Finally, we present an algorithm to compute the optimal order quantities.     

EOQ holds under stochastic demand,a technical note

We consider a variant of the economic order quantity (EOQ) model. Mainly, we assume that demand occurs at random, one unit at a time, and is characterized by independent and identically distributed times between two demand epochs. We also assume that the ordering policy is characterized by ordering the same amount whenever the inventory level drops to zero, and a demand occurs. Surprisingly, we show that the optimal order quantity that minimizes the expected inventory cost follows the familiar EOQ formula.     

An EOQ model for deteriorating items under supplier credits linked to ordering quantity

In the classical inventory economic order quantity (or EOQ) model, it was assumed that the purchaser must pay for the items received immediately. However, in practices, the supplier usually is willing to provide the purchaser a permissible delay of payments if the purchaser orders a large quantity. As a result, in this paper, we establish an EOQ model for deteriorating items, in which the supplier provides a permissible delay to the purchaser if the order quantity is greater than or equal to a predetermined quantity. We then characterize the optimal solution and provide an easy-to-use algorithm to find the optimal order quantity and replenishment time. Finally, several numerical examples are given to illustrate the theoretical results.     

A modified method to compute economic order quantities without derivatives by cost-difference comparisons

This note presents a modified method to compute economic order quantities without derivatives by cost-difference comparisons. Extensions to allow backorders are done for the EOQ/EPQ models. In contrast to previous literatures, limiting values on a finite planning horizon are used rather than algebraic manipulations for the cost function comparisons.     

Entropic order quantity (EnOQ) model for deteriorating items

Jaber et al. [M.Y. Jaber, R.Y. Nuwayhid, M.A. Rosen, Price-driven economic order systems from a thermodynamic point of view, Int. J. Prod. Res. 42 (24) (2004) 5167–5184] suggested that it might be possible to improve production systems performance by applying the first and second laws of thermodynamics to reduce system entropy (or disorder). They then used these laws to modify the economic order quantity (EOQ) model to derive an equivalent entropic order quantity (EnOQ). The results suggested that larger quantities should be ordered than is suggested by the classical EOQ model.     

An EOQ model for deteriorating items under trade credits

In the classical inventory economic order quantity (or EOQ) model, it was assumed that the supplier is paid for the items immediately after the items are received. However, in practices, the supplier may simultaneously offer the customer: (1) a permissible delay in payments to attract new customers and increase sales, and (2) a cash discount to motivate faster payment and reduce credit expenses. In this paper, we provide the optimal policy for the customer to obtain its minimum cost when the supplier offers not only a permissible delay but also a cash discount. We first establish a proper model, and then characterize the optimal solution and provide an easy-to-use algorithm to find the optimal order quantity and replenishment time. Furthermore, we also compare the optimal order quantity under supplier credits to the classical economic order quantity. Finally, several numerical examples are given to illustrate the theoretical results.     

Some comments on “A simple method to compute economic order quantities”

In this note, we emphasize that the arithmetic–geometric-mean-inequality approach proposed by Teng [Teng, J.T., 2008. A simple method to compute economic order quantities. European Journal of Operational Research. doi:10.1016/j.ejor.2008.05.019] is not a general solution method. Teng’s approach happens to work and give the correct results when the two terms in an objective function are any functions such that their product is a constant. The classical EOQ model works fine since the product of the two terms is indeed a constant! When the product is not a constant, Teng’s approach is of little use. This is exemplified in Comment 1 via solving the EOQ model with complete backorders (where the model is regarded as having two decision variables). Comment 2 is generally valid for an algebraic method when it is used to solve an objective function with two decision variables.     

Revisiting ROQ: EOQ for Company-wide ROI Maximization

Although attempts have been made in the past to modify the economic order quantity (EOQ) model to the maximization of return on investment (ROI), they either failed to take the whole enterprise into account, or reached the erroneous conclusion that no adaptation is required for that purpose. In this paper we develop the company-wide ROI maximizing order quantity, and show that it is bounded from above by EOQ and that it does not necessarily follow the square root of the demand level. In fact, there are conditions under which the order quantity is constant, regardless of the demand level, or even decreasing with demand. It is important to note that such a policy, if undertaken by many firms, will reduce the economic accelerator, and thus reduce the volatility of business cycles.     

基于数量折扣合同和缺货损失的EOQ模型的改进

经济订购批量模型假定需求率、单位持有成本、订货成本为常数下得到总成本最低的订购批量,这些参数常数化的假设在现实中通常难以满足.假定需求和订货费为不确定的、库存成本包括年固定成本(与订货量无关)和年可变成本(与订货量有关),用三角模糊数表示年需求和订货费,通过引入数量折扣合同来量化单位产品进价,分别在不允许缺货和考虑缺货损失两种情况下得到最佳订货量.最后的算例表明了模型的合理性.     

Weibull变质率和短缺量拖后的易变质物品EOQ模型

基于需求和采购价格均为时变的EOQ模型,考虑物品的变质率呈更符合现实情况的三参数Weibull分布,同时考虑短缺量拖后和资金时值对易变质物品库存管理的影响,构建了相应的EOQ模型.应用数学软件Matlab对该库存模型进行仿真计算和主要影响参数的灵敏度分析.结果表明,该模型存在最优解,且各主要影响参数对最优库存控制各有不同程度的影响,资金时值对库存总成本净现值的影响程度要甚于短缺量拖后的影响,故在制定科学的库存策略时资金时值需要更加关注.     

Improved rounding procedures for the discrete version of the capacitated EOQ problem

We consider a transportation problem where different products have to be shipped from an origin to a destination by means of vehicles with given capacity. The production rate at the origin and the demand rate at the destination are constant over time and identical for each product. The problem consists in deciding when to make the shipments and how to fill the vehicles, with the objective of minimizing the sum of the average transportation and inventory costs at the origin and at the destination over an infinite horizon. This problem is the well known capacitated EOQ (economic order quantity) problem and has an optimal solution in closed form. In this paper we study a discrete version of this problem in which shipments are performed only at multiples of a given minimum time. It is known that rounding-off the optimal solution of the capacitated EOQ problem to the closest lower or upper integer value gives a tight worst-case ratio of 2, while the best among the possible single frequency policies has a performance ratio of 5/3. We show that the 5/3 bound can be obtained by a single frequency policy based on a rounding procedure which considers classes of instances and, for each class, identifies a shipping frequency by rounding-off in a different way the optimal solution of the capacitated EOQ problem. Moreover, we show that the bound can be reduced to 3/2 by using two shipping frequencies, obtained by a rounding procedure, in one class of instances only.     

The impact of dynamic pricing on the economic order decision

This paper analyzes the impact of dynamic pricing on the single product economic order decision of a monopolist retailer. Items are procured from an external supplier according to the economic order quantity (EOQ) model and are sold to customers on a single market without competition following the simple monopolist pricing problem. Coordinated decision making of optimal pricing and ordering is influenced by operating costs – including ordering and inventory holding costs – and the demand rate obtained from a price response function. The retailer is allowed to vary the selling price, either in a fixed number of discrete points in time or continuously. While constant and continuous pricing have received much attention in the literature, problems with a limited number of price changes are rather rare. This paper illustrates the benefit of dynamically changing prices to achieve operational efficiency in the EOQ model, that is to trigger high demand rates when inventories are high. We provide structural properties of the optimal time instants when the price should be changed. Taking into account costs for changes in price, it provides numerical guidance on number, timing, and size of price changes during an order cycle. Numerical examples show that the benefits of dynamic pricing in an EOQ framework can be achieved with only a few price changes and that products being unprofitable under static pricing may become profitable under dynamic pricing.     

Supply chain scheduling with receiving deadlines and non-linear penalty

We study the operations scheduling problem with delivery deadlines in a three-stage supply chain process consisting of (1) heterogeneous suppliers, (2) capacitated processing centres (PCs), and (3) a network of business customers. The suppliers make and ship semi-finished products to the PCs where products are finalized and packaged before they are shipped to customers. Each business customer has an order quantity to fulfil and a specified delivery date, and the customer network has a required service level so that if the total quantity delivered to the network falls below a given targeted fill rate, a non-linear penalty will apply. Since the PCs are capacitated and both shipping and production operations are non-instantaneous, not all the customer orders may be fulfilled on time. The optimization problem is therefore to select a subset of customers whose orders can be fulfilled on time and a subset of suppliers to ensure the supplies to minimize the total cost, which includes processing cost, shipping cost, cost of unfilled orders (if any), and a non-linear penalty if the target service level is not met. The general version of this problem is difficult because of its combinatorial nature. In this paper, we solve a special case of this problem when the number of PCs equals one, and develop a dynamic programming-based algorithm that identifies the optimal subset of customer orders to be fulfilled under each given utilization level of the PC capacity. We then construct a cost function of a recursive form, and prove that the resulting search algorithm always converges to the optimal solution within pseudo-polynomial time. Two numerical examples are presented to test the computational performance of the proposed algorithm.