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.     

Managing a dual-channel supply chain under price and delivery-time dependent stochastic demand

Several leading manufacturers recently combined the traditional retail channel with a direct online channel to reach a wider range of customers. We examine such a dual-channel supply chain under price and delivery-time dependent stochastic customer demand. We consider five decision variables, the price and order quantity for both the retail and the online channels and the delivery time for the online channel. Uncertainty frequently arises in both retail and online channels and so additional inventory management is required to control shortage or overstock and that has an effect on the optimal order quantity, price, and lead time. We developed mathematical models with the profit maximization motive. We analyze both centralized and decentralized systems for unknown distribution function of the random variables through a distribution-free approach and also for known distribution function. We examine the effect of delivery lead time and customers’ channel preference on the optimal operation. For supply chain coordination a hybrid all-unit quantity discount along a franchise fee contract is used. Moreover, we use the generalized asymmetric Nash bargaining for surplus profit distribution. A numerical example illustrates the findings of the model and the managerial insights are summarized for centralized, decentralized, and coordinated scenarios.     

Multi-item inventory models with price dependent demand under flexibility and reliability consideration and imprecise space constraint: A geometric programming approach

In this paper, multi-item economic production quantity (EPQ) models with selling price dependent demand, infinite production rate, stock dependent unit production and holding costs are considered. Flexibility and reliability consideration are introduced in the production process. The models are developed under two fuzzy environments–one with fuzzy goal and fuzzy restrictions on storage area and the other with unit cost as fuzzy and possibility–necessity restrictions on storage space. The objective goal and constraint goal are defined by membership functions and the presence of fuzzy parameters in the objective function is dealt with fuzzy possibility/necessity measures. The models are formed as maximization problems. The first one—the fuzzy goal programming problem is solved using Fuzzy Additive Goal Programming (FAGP) and Modified Geometric Programming (MGP) methods. The second model with fuzzy possibility/necessity measures is solved by Geometric Programming (GP) method. The models are illustrated through numerical examples. The sensitivity analyses of the profit function due to different measures of possibility and necessity are performed and presented graphically.     

A study on the effect of yield uncertainty in price-setting newsvendor models with additive-multiplicative demand

Random yield and uncertain demand usually both exist in many industries, such as the semiconductor industry. In this paper, the price-setting newsvendor model is studied which involves a single manufacturer and a single retailer with random yield and uncertain demand respectively. Under the condition of additive-multiplicative demand, we investigate the varying effects of random yield on the optimal price, order quantity, and expected profit in two situations with different cost structures. The first case is an in-house production case where the firm pays for the raw material quantity it has ordered, and the second one is a procurement case where the firm pays for the real product quantity it receives only. By using the theory of stochastic comparisons, we find that a less variable and a stochastically larger yield rate both lead to a lower optimal price and a higher expected profit for the in-house production case. Moreover, a less variable yield rate also results in a lower optimal price and a higher profit for the procurement case, but this is not true for a stochastically larger yield rate. Numerical examples illustrate that the effect of yield randomness on the optimal order quantity is not general.     

A joint optimal pricing,rebate value,and lot sizing model

Delayed incentives in the form of mail-in cash rebates are very popular among manufacturers, and more recently, among retailers. One of the main advantages of rebates is that while they increase demand, a small proportion of consumers redeem them. In this paper, we formulate and solve models for jointly determining the optimal price, rebate face value, and the optimal order quantity for a price and rebate sensitive deterministic demand. The models show that under realistic conditions, offering rebates can have significant pricing and inventory policy implications and can lead to a significant increase in profit.     

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.     

单向可替代产品价格和库存的联合决策

考虑单周期问题中零售商同时销售两种可单向替代的产品,以期望利润为目标函数建立数学模型.将库存和替代价格共同作为零售商决策变量,证明其目标函数是凹函数,并得到求模型最优解的充要条件及解存在的范围.最后假设产品需求为正态分布,通过数值实验对模型的最优解进行分析,结果表明:实行最优替代价格策略可以有效提高零售商期望利润;允许替代销售不一定提高市场服务水平;被替代产品的销售价格和残值对零售商的最优替代价格决策没有显著影响.     

The implications of costs, capacity, and competition on product line selection

We consider a situation in which a manufacturer has to select the product(s) to sell as well as the selling price and production quantity of each selected product. There are two substitutable products in the consideration set, where product 2 has a higher quality and reservation price than that of product 1. By considering the cannibalization effect that depends on the selling price of each product, the manufacturer needs to evaluate the profit function associated with three different product line options: sell both products or only one of the 2 products. In order to examine the impact of costs, capacity, and competition on the optimal product line selection, optimal price, and optimal production quantity analytically, we present a stylized model in this paper so that we can determine the conditions under which a particular option is optimal.     

The EOQ with defective items and partially permissible delay in payments linked to order quantity derived algebraically

Most researchers established their inventory lot-size models under trade credit financing by assuming that the supplier offers the retailer fully permissible delay in payments and the products received are all non-defective. However, in the real business environment, it often can be observed that the supplier offers the retailer a fully permissible delay in payments only when the order quantity is greater than or equal to the predetermined quantity Q _d . In addition, an arriving order lot usually contains some defective items due to imperfect production processes or other factors. To capture this reality, the paper extends Huang (2007) economic order quantity (EOQ) model with partially permissible delay in payments to consider defective items. We formulate the proposed problem as a profit maximization EOQ model in which the replenishment cycle time is the decision variable. Then we use the arithmetic-geometric mean inequality approach to determine the optimal solution under various situations. An algorithm to obtain the optimal solution is also provided. Finally, the numerical examples and sensitivity analysis are given to illustrate the results.     

The optimal pricing and ordering policy for an integrated inventory model when trade credit linked to order quantity

In traditional inventory models, it is implicitly assumed that the buyer must pay for the purchased items as soon as they have been received. However, in many practical situations, the vendor is willing to provide the buyer with a permissible delay period when the buyer’s order quantity exceeds a given threshold. Therefore, to incorporate the concept of vendor–buyer integration and order-size-dependent trade credit, we present a stylized model to determine the optimal strategy for an integrated vendor–buyer inventory system under the condition of trade credit linked to the order quantity, where the demand rate is considered to be a decreasing function of the retail price. By analyzing the total channel profit function, we developed some useful results to characterize the optimal solution and provide an iterative algorithm to find the retail price, buyer’s order quantity, and the numbers of shipment per production run from the vendor to the buyer. Numerical examples and sensitivity analysis are given to illustrate the theoretical results, and some managerial insights are also obtained.     

The effect of supply uncertainty in price-setting newsvendor models

We consider a price-setting newsvendor model in which a firm needs to make joint inventory and pricing decisions before the selling season. The supply process is uncertain such that the received quantity is the product of the order quantity and a random yield rate. Two cost structures are investigated, the in-house production case in which the firm pays for the input quantity and the procurement case in which the firm pays for the quantity received only. Our objective is to investigate the effect of yield randomness on optimal decisions and expected profit. By using the theory of stochastic comparisons, we find that under both cost structures, a less variable yield rate leads to a lower optimal price and a higher expected profit. Moreover, we show that in the in-house production case, a stochastically larger yield rate also results in a lower optimal price and a higher profit, but this is not true in the procurement case. Examples show that the effect of supply uncertainty on optimal order quantity is not universal.     

The setting of profit targets for target oriented divisions

Setting profit targets and striving to achieve them is fundamental to business survival and success. However, there has been little research on modeling profit-target setting. In this paper, we study analytic target setting under a common business scenario where a firm is in control of multiple divisions. Both the firm and the divisions maximize the profit probability, i.e., the probability of achieving some given profit target. The firm sets a profit target for each division which then acts as a price-setting newsvendor. We first obtain the optimal order quantity, the optimal retail price, and the maximal profit probability of a single division given its assigned target. We then derive the firm’s profit probability and focus on two specific cases to gain more managerial insights. In the first case of fair target setting, we show that when each division’s demand distribution has an increasing failure rate, if a division has a relatively high (low) production cost, its assigned profit target decreases (increases) with regard to its price elasticity. In the second case, if the firm is in control of two identical divisions, each division’s optimal profit target is just half of the firm’s profit target when the price elasticity is two or more, regardless of production cost and demand distribution.     

需求依赖销售努力库存系统的随机比较

研究需求依赖销售努力库存系统中需求不确定性对系统最优订货量、利润和销售努力的影响.对一般需求模型给出期望利润关于订货量和努力水平为联合凹的充分条件,证明期望利润函数的超模性质.对加乘需求模型证明系统最优利润和最优努力水平都可由一类与需求分布有关的广义TTT变换来表示.通过引入定义在不同支撑分布集合上一阶、二阶和三阶随机占优,得到广义TTT变换之差与二阶和三阶随机占优之间的关系式,建立了比较库存系统最优利润或努力水平的理论基础.在一阶和二阶随机占优意义下对加乘需求模型得到比较系统最优利润和努力水平的充分条件或充分必要条件.进一步,证明存在一类需求分布当系统关键比(或市场价格)足够大时系统最优利润和努力水平随需求可变性的增加而增加.最后给出几个数值例子验证了研究结果.     

需求替代下易腐品的订货策略和定价策略研究

针对蔬菜、水果等这类在存储的过程中随时间的推移会发生大量损耗的易腐品,在激烈的市场竞争中,产品的需求不仅与本身的价格有关,而且与竞争对手产品的价格有关,零售商根据市场需求确定最优定价和订货策略以最大化自身利益,建立库存模型,证明了模型存在唯一最优策略.通过数值实验,分析得到替代程度发生变化对最优策略的影响.     

不确定需求与产出供应链回购契约决策

针对市场需求的不确定性和供应商产出产品合格率的不确定性,提出供应商产出量小于销售商订购量时需再生产满足销售商的订购,以及供应商生产过量和回购的产品通过折扣市场出售,建立以供应链期望利润为目标函数,以回购单价为决策变量的供应链回购契约决策模型.通过模型的分析,证明了模型存在最优的期望利润,给出了最优回购单价满足的方程;同时,也证明了最优订购量,最优生产量和销售商最优期望利润是回购单价的增函数.最后,通过算例验证了模型的有效性.     

Wholesale pricing and evolutionarily stable strategies of retailers with imperfectly observable objective

This paper develops a one-population (indirect) evolutionary game model of a supply chain with one manufacturer/supplier and many (a sufficiently large number of) retailers to study how the retailer’s marketing objective depends on the wholesale price, its observability, the error probability of the observed result on the rival’s preference, the market scale and the retailer’s bargaining power. This paper also presents an algorithm for computing the optimal wholesale price of the manufacturer. We find that the profit (revenue) maximization behavior is an evolutionarily stable marketing strategy if the wholesale price is sufficiently high (low). Given an appropriate wholesale price, the revenue maximization behavior coexists with the profit maximization behavior in the retailers’ population. The larger the market scale, the stronger the motivation of the retailer to take profit maximization behavior due to a higher wholesale price. The cross effects of the retailer’s reservation payoff and the other factors should be considered in the decision process.     

基于腐损程度的季节性产品动态定价与订单量的集成优化

为了对易腐季节性产品的销售价格和订单量进行最优决策,考虑产品在不同腐损程度的情形下,需求与价格和时间同时相关的一类季节性产品的动态定价和订单量的集成优化问题.建立该类产品的价格制订次数、每次制订的价格和订单量的集成优化模型,并对模型进行求解,最后结合数例验证模型的实用性和可操作性,并分析产品腐损程度对价格制订次数、价格大小、订单量和利润的影响.结果表明,随着产品腐损程度的提高,零售商在销售季节内的产品价格最优制订次数保持不变;零售商在销售季节内所制订的最优价格逐渐微降;产品的最优订单量和所产生的最优利润逐渐微升.     

The role of retailer’s performance in optimal wholesale price discount policies

The main goal of this paper is to model the effects of wholesale price control on manufacturer’s profit, taking explicitly into account the retailer’s sales motivation and performance. We consider a stylized distribution channel where a manufacturer sells a single kind of good to a single retailer. Wholesale price discounts are assumed to increase the retailer’s motivation thus improving sales. We study the manufacturer’s profit maximization problem as an optimal control model where the manufacturer’s control is the discount on wholesale price and retailer’s motivation is one of the state variables. In particular in the paper we prove that an increasing discount policy is optimal for the manufacturer when the retailer is not efficient while efficient retailers may require to decrease the trade discounts at the end of the selling period. Computational experiments point out how the discount on wholesale price passed by the retailer to the market (pass-through) influences the optimal profit of the manufacturer.     

Coordination strategies in a three-echelon reverse supply chain for economic and social benefit

In addition to seeking profit maximization, reverse supply chains should further seek to maximize social benefit. Consequently, this paper investigates the coordination strategies among different parties in a three-echelon reverse supply chain consisting of a single collector, a single remanufacturer, and two retailers with complete information sharing. Additionally, this paper discusses four coordination strategies and performs a detailed comparative analysis on the optimal decisions of different models. Three numerical analyses are performed to show how the potential market demand of remanufactured products and the utilization ratio of used products affect the optimal total channel profit, recycle quantity and retail prices among four models in a reverse supply chain. The results indicate that optimal total channel profit and recycle quantity in a reverse supply chain are maximized in a centralized model. With the same potential market demand of remanufactured products and utilization ratio of used products, a centralized model maximizes the economic and social benefit compared to the other three models.     

Integrated pricing and lot-sizing decisions in a serial supply chain

In this article, we consider a serial supply chain controlled by a decision-maker who is responsible for deciding the amount of raw material to order from the selected suppliers, the amount of product to transfer between consecutive stages in order to avoid any inventory shortages, and the final product's selling price so that the profit per time unit is maximized. Coordinating all these decisions simultaneously is a topic that has been neglected in literature. This integrated process is modeled as a mixed-integer nonlinear programming model. In addition, the model requires the order quantity received from each selected supplier to be an integer multiple of the order quantity delivered to the following stage, which means that a different multiplicative factor can be assigned to each supplier. This coordination mechanism shows an improvement in the objective function compared to existing models that assign the same multiplicative factor to each selected supplier. Moreover, we develop a heuristic algorithm that generates near optimal solutions in a timely manner. Two numerical examples are presented to illustrate the proposed model and the heuristic algorithm.