考虑事故风险损失的爆炸物品经济订货批量模型研究

爆炸物品在储存过程中存在发生爆炸事故,从而给人类和环境带来伤害的可能,因此在对爆炸物品进行采购决策时必需考虑由此带来的风险损失.在给出爆炸物品事故风险损失度量方法的基础上,建立了爆炸物品的经济订货批量模型,证明了模型存在唯一最优解,并给出了模型的求解步骤,为相关企业合理制定采购决策提供了理论依据.数字算例分析了事故概率、赔偿标准、单位库存费、单次采购费对最优批量的影响,比较了考虑事故风险损失与否时的最优批量,结果表明,当事故概率或赔偿标准较高时,两者对应的最优批量差异明显.这也说明,当事故概率或赔偿标准达到一定程度时,考虑事故风险损失是十分必要的.     

Optimal purchase of two-itemized drugs for a disease

This paper submits a mathematical model called the two-itemized drugs purchasing decision (TDPD) model to conduct the optimal purchase of two-itemized drugs for healing a given disease. This TDPD model considers not only the annual estimated number of patients suffering from the given disease, the treatment courses, and the unit profit of each drug, but also the strength of the patient's perception on treatment quality, the different purchasing price of each drug with quantity discounts, the ordering cost, the holding cost, and other related costs to determine the optimal order quantity of each drug for achieving the maximum profit. A computerized solving program proposed in this paper applies tabu search technique as the main program and the all-units quantity discounts for economic order quantity as the sub-program to solve such a combinatorial problem, as well as perform sensitivity analyses on the changes by the strength of the patient's perception on treatment quality and the changes of annual estimated number of patients for the given disease. Two drugs, Lipitor and Gemnpid, to heal a disease ‘Hyperlipidaemia’ are considered as a case example in this study. This paper contributes a prototype quantitative method of purchasing decision for a given disease to a decision-maker with profound insights.     

Economic order quantity model and Taguchi’s cost of poor quality

In this paper we consider defective products and Taguchi’s cost of poor quality in the economic order quantity (EOQ) model. We assume that the product quality performs a normal distribution function, and the Taguchi’s poor quality cost has been involved. From our analysis, it has been found that the annual profit will be decreased if the poor quality of product and Taguchi’s quality cost are involved in the model. It has also been found that economic order quantity in our model is larger than that in a traditional EOQ model.     

带有交易费用和持有成本的局内采购管理模型竞争分析

采购管理是企业经营活动的一个重要组成部分,更加有效的采购管理策略可以大大减少采购费用,对于企业的经营业绩非常重要。在现实的经济活动中交易费用和持有成本在企业管理费用中占很大一部分比率,而采购过程影响着交易费用和持有成本。所以在前人研究的基础上,将交易费用和持有成本引入到局内采购管理模型中,使得运用该策略无论以后采购价格如何变化,局内人的采购成本总是对应局外问题最优采购成本的一定比例c之内,并得到c与原模型相同。但是引入交易费用和持有成本后每天的采购量将发生变化,原模型是在不考虑交易费用和持有成本的前提下得得到的每天采购量和最优竞争比,如果考虑到现实经济活动中不可忽略的交易费用和持有成本,仍然按照原模型来确定每天的采购量来采购就不能得到最优竞争比c。所以本文考虑到了交易费用和持有成本,并得到和原模型不同的每天采购量,并求出最优竞争比c。     

Optimal inventory policies under decreasing cost functions via geometric programming

In this paper, we establish and analyze two economic order quantity (EOQ) based inventory models under total cost minimization and profit maximization via geometric programming (GP) techniques. Through GP, optimal solutions for both models are found and managerial implications on the optimal policy are determined through bounding and sensitivity analysis. We investigate the effects on the changes in the optimal order quantity and the demand per unit time according to varied parameters by studying optimality conditions. In addition, a comparative analysis between the total cost minimization model and the profit maximization model is conducted. By investigating the error in the optimal order quantity of these two models, several interesting economic implications and managerial insights can be observed.     

Minimum Cost Allocation of Tenders

In a big organization like the Australian Post Office, where large sums of money are spent to purchase a very large number of items every financial year, the problem is that of allocating the orders of the different items to the competing tenderers at a minimum cost. We have dealt with this in two sections; one is devoted to quantity discounts, the other to order value discounts. We have shown the mathematical formulation using integer and mixed integer linear programming, the mathematical programming systems used, the benefits gained and costs incurred, and the effects of the implementation of minimum cost allocation techniques on the organizational structure of some sections of the A.P.O. We have also shown that these techniques could be used to analyse the relative economic efficiencies of the competing tenderers with the objective of formulating a suitable economic purchasing policy for the organization concerned.     

装配型企业订货量分配与订单排产联合决策研究

针对供应商交货数量不确定环境下,多品种小批量装配型制造企业因生产物料不配套造成生产计划不可行甚至客户订单拖期的问题,从企业运作整体出发,考虑订货量分配决策对订单生产和交货的影响,以最小化采购成本和最小化订单排产相关成本为优化目标,在允许零部件拖期交货且供应商提供拖期价格折扣条件下,建立订货量分配与订单排产联合优化模型。针对可行解空间巨大、传统数学规划方法难以求解的问题,从增强搜索性能角度出发,设计基于自定义邻域搜索算子的局部搜索机制和基于随机与种群重构变异机制的改进粒子群算法的模型求解策略。通过应用实例对本文模型和算法进行了有效性验证和灵敏度分析,结果表明,相比于传统的分散决策方案,本文模型能够有效降低整体成本水平,引入的改进机制能够显著提升算法搜索性能,为企业供应风险下的运营决策制定提供理论参考。     

A fuzzy mathematical model for the joint economic lot size problem with multiple price breaks

This paper applies fuzzy mathematical programming to solve the joint economic lot size problem with multiple price breaks. In order to entice the buyer to increase the order quantity, it is a common practice for the seller to offer quantity discounts to the buyer. From the system viewpoint, the joint cost for the seller and buyer can be minimized only when the buyer increases his economic order quantity. The problem is how to determine the number of price breaks, as well as the quantity discount and order quantity at each price break, to achieve the optimal joint cost. Fuzzy mathematical programming provides a very efficient algorithm to solve the above problem simultaneously from the perspectives of the seller and the buyer. Another common problem in joint economic lot size model is how to split the system profit between the seller and the buyer. Whereas the traditional approach to this problem is to divide the profit based on a certain ratio determined by the bargaining power of both parties, fuzzy mathematical programming can achieve the same satisfaction level to both parties based on their respective cost functions.     

Sensitivity analysis of the newsvendor model

Quality of decisions in inventory management models depends on the accuracy of parameter estimates used for decision making. In many situations, error in decision making is unavoidable. In such cases, sensitivity analysis is necessary for better implementation of the model. Though the newsvendor model is one of the most researched inventory models, little is known about its robustness. In this paper, we perform sensitivity analysis of the classical newsvendor model. Conditions for symmetry/skewness of cost deviation (i.e., deviation of expected demand–supply mismatch cost from its minimum) have been identified. These conditions are closely linked with symmetry/skewness of the demand density function. A lower bound of cost deviation is established for symmetric unimodal demand distributions. Based on demonstrations of the lower bound, we found the newsvendor model to be sensitive to sub-optimal ordering decisions, more sensitive than the economic order quantity model. Order quantity deviation (i.e., deviation of order quantity from its optimum) is explored briefly. We found the magnitude of order quantity deviation to be comparable with that of parameter estimation error. Mean demand is identified as the most influential parameter in deciding order quantity deviation.     

Determining optimal order splitting and reorder level for N-supplier inventory systems

This paper considers multiple-supplier single-item inventory systems, where the item acquisition lead times of suppliers and demand arrival are random, and backorder is allowed. The acquisition takes place when the inventory level depletes to a reorder level, and the order is split among multiple suppliers. The acquisition lead times may have different distributions, the unit purchasing prices from suppliers may be different, and thus the order quantities for different suppliers may be different. The problem is to determine the reorder level and order quantity for each supplier so that the expected total cost per unit time, consisting of the fixed ordering cost, procurement cost, inventory holding cost and shortage cost, is minimized. We develop a mathematical model describing the system in detail. We also conduct extensive numerical experiments to analyze the advantages and distinct characteristics of multiple-supplier systems.     

Analysis of a fuzzy economic order quantity model for deteriorating items under retailer partial trade credit financing in a supply chain

This paper investigates the economic order quantity (EOQ) — based inventory model for a retailer under two levels of trade credit to reflect the supply chain management situation in the fuzzy sense. It is assumed that the retailer maintains a powerful position and can obtain the full trade credit offered by the supplier yet the retailer just offers a partial trade credit to customers. The demand rate, holding cost, ordering cost, purchasing cost and selling price are taken as fuzzy numbers. Under these conditions, the retailer can obtain the most benefits. Study also investigates the retailer’s inventory policy for deteriorating items in a supply chain management situation as a cost minimization problem in the fuzzy sense. The annual total variable cost for the retailer in fuzzy sense is defuzzified using Graded Mean Integration Representation method. Then the present study shows that the defuzzified annual total variable cost for the retailer is convex, that is, a unique solution exists. Mathematical theorems and algorithms are developed to efficiently determine the optimal inventory policy for the retailer. Numerical examples are given to illustrate the theorems and the algorithms. Finally, the results in this paper generalize some already published results in the crisp sense.     

Robust economic order quantity models

In this paper, we study the classical economic order quantity (EOQ) model under significant. In particular, the problem under consideration is the economic order quantity model with the input data of the demand rate, the order cost, and the holding cost rate being uncertain. A robustness approach based on scenario characterization of the input data is adopted to describe the uncertainties. The aim of the approach is to find an inventory policy that performs well under all realizable input data scenarios. An efficient linear time algorithm is devised to find the robust decisions. Analytical results are obtained for the case where input data are defined in continuous intervals. Comparisons on performances between the robust decisions and the stochastic optimization decisions are conducted. The results demonstrate the advantages of robustness approach.     

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.     

Optimal inventory policies for an economic order quantity model with decreasing cost functions

In this paper, three total cost minimization EOQ based inventory problems are modeled and analyzed using geometric programming (GP) techniques. Through GP, optimal solutions for these models are found and sensitivity analysis is performed to investigate the effects of percentage changes in the primal objective function coefficients. The effects on the changes in the optimal order quantity and total cost when different parameters of the problems are changed is also investigated. In addition, a comparative analysis between the total cost minimization models and the basic EOQ model is conducted. By investigating the error in the optimal order quantity and total cost of these models, several interesting economic implications and managerial insights can be observed.     

Integrated inventory model with quantity discount and price-sensitive demand

Quantity discount has been a subject of study for a long time; however, little is known about its effect on integrated inventory models when price-sensitive demand is placed. The objective of this study is to find the optimal pricing and ordering strategies for an integrated inventory system when a quantity discount policy is applied. The pricing strategy discussed here is one in which the vendor offers a quantity discount to the buyer. Then, the buyer will adjust his retail price based on the purchasing cost, which will influence the customer demand as a result. Consequently, an integrated inventory model is established to find the optimal solutions for order quantity, retail price, and the number of shipments from vendor to buyer in one production run, so that the joint total profit incurred has the maximum value. Also, numerical examples and a sensitivity analysis are given to illustrate the results of the model.     

Improving the efficiency of the purchasing process using total cost of ownership information: The case of heating electrodes at Cockerill Sambre S.A.

Improving the efficiency of the purchasing process provides important opportunities to increase a firm's profitability. In this paper we introduce a mathematical programming model that uses total cost of ownership information to simultaneously select suppliers and determine order quantities over a multi-period time horizon. The total cost of ownership quantifies all costs associated with the purchasing process and is based on the activities and cost drivers determined by an activity based costing system. Our approach is motivated by the purchasing problem of heating electrodes at Cockerill Sambre, a Belgian multinational steel producer. In this case quality issues account for more than 70% of the total cost of ownership making the quality of a supplier a critical success factor in the supplier selection process.     

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.     

Channel coordination under two-level trade credits and demand uncertainty

This study considers a decentralized supply chain where a retailer has an opportunity to order a product from a supplier prior to the sales season to satisfy uncertain demand. The retailer provides trade credit to end customers and makes credit period and order quantity decisions to maximize profits. The end demand is both random and credit period-dependent. On the basis of the newsvendor model, this paper focuses on channel coordination when a retailer provides trade credit to end customers. When the supplier also provides trade credit to the retailer, we show that the traditional trade credit contract cannot coordinate the channel. Four composite contracts based on trade credit (trade credit cost sharing with buy back or quantity flexibility; modified trade credit with buy back or quantity flexibility) are provided to induce the retailer to make decisions while optimizing the channel profit. This paper shows that the retailer provides a longer credit period to its customers and orders a larger quantity from the supplier under the composite contracts. With these contracts, the profit sharing between both parties depends on the wholesale price (Pareto improvement) for the fixed retail price and the purchasing cost.     

Optimal Ordering Policy for Deteriorating Items with Partial Backlogging under Permissible Delay in Payments

In 1985, Goyal developed an Economic order quantity (EOQ) model under conditions of permissible delay in payments. Jamal et al. then generalized Goyal’s model for deteriorating items with completely backlogging. However, they only ran several simulations to indicate that the total relevant cost may be convex. Recently, Teng amended Goyal’s model by considering the difference between unit price and unit cost, and provided an alternative conclusion that it makes economic sense for some retailers to order less quantity and take the benefits of the permissible delay more frequently. However, he did not consider deteriorating items and partial backlogging. In this paper, we establish a general EOQ model for deteriorating items when the supplier offers a permissible delay in payments. For generality, our model allows not only the partial backlogging rate to be related to the waiting time but also the unit selling price to be larger than the unit purchase cost. Consequently, the proposed model includes numerous previous models as special cases. In addition, we mathematically prove that the total relevant cost is strictly pseudo-convex so that the optimal solution exists and is unique. Finally, our computational results reveal six managerial phenomena.     

Optimizing a Production System with a Fixed Delivery Schedule

This note considers a model in which a manufacturing company purchases a raw material, manufactures a product (at a finite rate) and ships a fixed quantity of the product to a single customer at fixed and regular intervals of time, as specified by the customer. In general there are several shipments made during each production run. The objective is to determine a purchasing and production schedule which minimises the total cost of purchasing, manufacturing and stockholding. It extends previously published work by considering the possibility that a single raw material purchase provides stock for several production runs or that several raw material purchases provide stock for a single production run.