快速补货模式下的动态定价与库存联合策略

在供应有限的情况下,研究常规补货和快速补货下商品动态定价问题.首先,建立了动态规划模型,理论证明了最优库存策略是基于(s,S)策略下改进的基本库存策略.其次,提出了一种启发式策略求复杂系统的最优策略,启发式算法能够求出最优价格和最优库存水平.最后,数值算例研究表明,库存管理中采用快速补货提高了零售商的利润;初始库存水平越高零售商的利润越高.     

允许缺货且带数量折扣的腐烂物质库存模型

在短缺量拖后率是等待时间的负指数函数、订购成本是批量的线性函数的条件下,建立了带数量折扣的腐烂物质库存模型,目标是优化总平均利润.在给定销售价格的情况下,证明了库存系统的最优补货策略存在且唯一;且若采用最优补货策略,平均利润函数是销售价格的凹函数;最后给出了模型的算法,并用数值例子说明了模型和算法的有效性.     

考虑顾客退货和固定成本的联合补货与定价策略

为了吸引更多顾客,许多电子商务零售商允许顾客在一定时间内退货,导致其利润明显减少。同时,在补货时不仅产生依赖补货量的变动成本,而且会产生与补货量无关的固定成本。基于此,以最大化电子商务零售商的利润为目标,建立考虑顾客退货和固定成本的联合补货与定价模型,其中顾客的退货量与满足的需求呈正比。在一般需求情形下,部分刻画多期问题的最优策略;在特殊需求情形下,证明(s,S,p)策略对单期问题最优,并对多期问题的最优策略进行严格刻画。根据已有刻画为多期问题构造启发式策略。数值结果表明启发式策略近似最优;当初始库存水平足够高/低时,最优补货水平和定价随退货率与固定成本单调变化。关键词:联合补货与定价模型;顾客退货;固定成本;随机动态规划;最优策略     

基于收益共享契约的零售商押金补货策略研究

押金补货是指零售商在第一阶段向供应商交纳一定的押金,在接下来的阶段中不需要再交纳额外的补货费用的补货方式。对于中小型零售商,它的补货策略往往受到自有资金的约束,当自有资金不足以订到报童模型的最优补货量时,不仅自身收益受到影响,还会影响到整条供应链的收益,本文研究了在随机市场需求,且零售商能够随时向银行贷款的情况下,基于收益共享契约的零售商的押金融资订货策略。本文从两阶段出发,分析零售商的最优订货策略,研究表明,零售商的补货策略受初始资产和收益共享系数的影响。最后,文章将其扩展到多阶段问题进行讨论。     

考虑资源约束和数量折扣的联合补货-选址库存协同优化研究

本文构建了一种基于联合补货策略的配送中心选址-库存协同优化新模型,该模型允许缺货,有资源约束且考虑数量折扣;同时设计了一种融合模拟退火思想的双种群独立进化的自适应差分算法(Adaptive Simulated Annealing Differential Algorithm,ASADE)对该模型进行求解,并通过算例与自适应差分算法、改进的蛙跳算法进行对比,证实了ASADE算法的有效性。最后进行了敏感性分析,讨论相关参数变动对总成本的影响,可为管理者更好决策提供有益的依据。     

具有Weibull生存死亡特征的冷链品库存补货定价策略研究

建立了无限期内冷链品具有Weibull生存死亡特征、随机需求且受售价影响的库存补货定价模型,其中售价是连续变化的,需求率是售价的指数函数,变质率服从的三参数Weibull分布,提前期固定。系统以利润最大化为目标函数,在(r,Q)库存策略下,建立库存模型,采用直接法,对模型近似求解,得到最优补货定价策略。利用Matlab进行算例模拟和灵敏度分析发现:补货提前期和单位仓储成本对补货定价策略影响较大,二者增大会导致系统利润降低;单位处理成本的增加,在一定程度上使得系统降低最优补货量,使系统利润增加;保鲜期固定的前提下,受冷链品的流动环境因子和存储环境因子影响的变质率对补货定价策略影响较大,它的增大会使系统利润降低。这些发现能够帮助优化系统模型,对现实问题具有一定的指导意义。     

基于(Q,r)补货策略的寄售库存模式研究

本文运用数学建模和数值分析的方法研究了基于(Q,r)补货策略的寄售库存模式中合同参数的优化问题。在该模式下,供应商确定Q、r值,并维持(z,Z)的库存水平,零售商对低于下限z或超过上限Z的库存收取罚金b。研究结果表明,零售商可以通过设置合理的罚金b来激励供应商选择合理的r和Q,使得最低的期望库存水平高于z,并且使成本达到最优。     

基于CRE的供应链渠道协作利润优化研究

为了实现供应链合作伙伴的双赢和多赢,在由一个制造商和两个批发商组成的供应链中,以制定最优共同补货周期策略为核心,制造商作为盟主指定共同补货周期和折扣率,批发商作为成员企业按共同补货同期的整数倍进行补货.制造商采用一致价格折扣的方式弥补批发商成本的增加.考虑到需求的可变性和是否实行共同补货周期策略,建立了制造商、批发商和整个供应链系统的利润优化模型并进行了模拟.结果表明共同补货周期策略可以实现多方收益的帕累托改进,供应链三方协作追求整体收益,可以实现"共赢".     

季节性供应链零售商补货策略研究——基于牛鞭效应视角

通过建立含有季节性自回归移动平均需求过程的供应链,零售商采用最小均方差预测技术预测提前期需求,分析(R,D)、(R,S)、(R,βS)、(R,γO)和(R,γO,βS)五种补货策略下的牛鞭效应.研究结果表明:(R,γO)补货策略是弱化牛鞭效应的最优补货策略,然而(R,γO)补货策略时出现了反牛鞭效应,无法保证供应链的安全供给.实践中当库存量调节系数和订货量调节系数较大时,(R,βS)补货策略能有效弱化牛鞭效应,当库存量调节系数和订货量调节系数较小时,(R,γO,βS)补货策略能有效弱化牛鞭效应;对于(R,βS)和(R,γO,βS)补货策略,牛鞭效应随着库存平滑系数的增大而增大;对于(R,γO)和(R,γO,βS)补货策略,牛鞭效应随着订货平滑系数的增大而增大;对于(R,S)、(R,βS)和(R,γO,βS)补货策略,牛鞭效应随着订货提前期的增大而增大;对于(R,γO)和(R,γO,βS)补货策略,牛鞭效应随着时刻t的增大而增大,但时刻t增大到一定程度时,牛鞭效应值基本不变.     

随机补货间隔且需求依赖库存水平的库存控制模型

定期补货库存模型在实践中被广泛使用,尤其是在单一供应商中购买多种不同产品的库存系统中更为常见.然而,大多数定期补货库存模型都假设补货的时间间隔是恒定不变的.但在实践中,补货的时间间隔也可能是一个随机的时间长度.提出了一个随机补货时间间隔和需求依赖于当前展示库存水平的库存控制模型,且补货间隔服从指数分布和均匀分布,同时允许短缺发生并且短缺量部分延期供给,并研究了模型最优解的存在性与唯一性.最后,给出了数值算例来说明模型在实际中的应用.     

A queuing approach for inventory planning with batch ordering in multi-echelon supply chains

This paper presents stylized models for conducting performance analysis of the manufacturing supply chain network (SCN) in a stochastic setting for batch ordering. We use queueing models to capture the behavior of SCN. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies . In the first case, we model one manufacturer with one warehouse, which supplies to various retailers. We determine the optimal inventory level at the warehouse that minimizes total expected cost of carrying inventory, back order cost associated with serving orders in the backlog queue, and ordering cost. In the second model we impose service level constraint in terms of fill rate (probability an order is filled from stock at warehouse), assuming that customers do not balk from the system. We present several numerical examples to illustrate the model and to illustrate its various features. In the third case, we extend the model to a three-echelon inventory model which explicitly considers the logistics process.     

An efficient algorithm for a generalized joint replenishment problem

In most multi-item inventory systems, the ordering costs consist of a major cost and a minor cost for each item included. Applying for every individual item a cyclic inventory policy, where the cycle length is a multiple of some basic cycle time, reduces the major ordering costs. An efficient algorithm to determine the optimal policy of this type is discussed in this paper. It is shown that this algorithm can be used for deterministic multi-item inventory problems, with general cost rate functions and possibly service level constraints, of which the well-known joint replenishment problem is a special case. Some useful results in determining the optimal control parameters are derived, and worked out for piecewise linear cost rate functions. Numerical results for this case show that the algorithm significantly outperforms other solution methods, both in the quality of the solution and in the running time.     

A multi-product multi-echelon inventory control model with joint replenishment strategy

On the basis of analyzing the shortages of present studies on multi-echelon inventory control, and considering some restrictions, this paper applies the joint replenishment strategy into the inventory system and builds a multi-product multi-echelon inventory control model. Then, an algorithm designed by Genetic Algorithm (GA) is used for solving the model. Finally, we respectively simulate the model under three different ordering strategies. The simulation result shows that the established model and the algorithm designed by GA have obvious superiority on reducing the total cost of the multi-product multi-echelon inventory system. Moreover, it illustrates the feasibility and the effectiveness of the model and the GA method.     

Temporary price increase during replenishment lead time

Pricing and inventory management make up together revenue management, which is a significant effort to boost revenues out of available resources. Firms use various forms of dynamic pricing, including personalized pricing, markdowns, promotions, coupons, discounts, and clearance sales, to respond to market fluctuations and demand uncertainty. In this paper, we study a temporary price increase policy, a form of dynamic pricing, for a non-perishable product, a practice used by several giant retailers such as Amazon, Walmart, and Apple. We develop a continuous review inventory model that allows for joint replenishment and pricing decisions, where the lead time is not zero. A replenishment decision controls supply, while a pricing decision controls demand. A manager exercises a temporary price increase to slow demand and avoid a stock-out situation while waiting for a shipment, which may not necessarily increase revenues, but decrease stock-out costs. The problem is to solve for the optimal replenishment and the pricing policy parameters that maximize the long-run expected profit. That is, when and how much to order and when to raise the price. In this paper, the inventory level and time trigger a price increase. We solve many numerical examples and perform extensive sensitivity analyses. Our results show that compared to a model that focuses on fixed pricing, our model brings an additional increase in profit of about 13%.     

风险厌恶条件下竞争报童问题的二层规划模型

有效应用数学规划方法研究报童类产品的库存管理,能够降低企业的成本和风险,从而提高企业的经济效益.此类问题的研究,目前主要集中在应用Nash博弈研究竞争报童问题以及零售商所持风险态度对供应链库存水平的影响.试图研究序贯决策下的竞争报童问题模型以及零售商所持风险态度对供应链库存水平的影响.由此建立了二层规划模型.算例表明序贯决策的竞争报童问题中,总订购量随风险厌恶程度的提高而降低.     

A minimax distribution-free procedure for a newsvendor problem with free shipping

In this paper, we study the optimal policies of retailers who operate their inventory with a single period model (i.e., newsvendor model) under a free shipping offer where a fixed shipping fee is exempted if an order quantity is greater than or equal to a given minimum quantity. Zhou et al. (2009) have explored this model, and we further investigate their analysis for the optimal ordering policies which they did not sufficiently develop. Based on the investigation, we extend the base model in order to deal with the practically important aspect of inventory management when the exact distribution function of demand is not available. We incorporate the aspect into the base model and present the optimal policies for the extended model with a numerical example. Finally, we conduct extensive numerical experiments to evaluate the performance of the extended model and analyze the impacts of minimum free shipping quantity and the fixed shipping fee on the performance.     

Congruential Inventory Model for Two-Echelon Distribution Systems

Large-scale inventory-distribution systems typically comprise a hierarchy of warehouses that stock goods for distribution to retailers at which demand for these goods originates. This paper develops an inventory model for two-echelon distribution systems under the assumption that the central warehouse and retailers order periodically. Characteristics of the optimal policy are described. An iterative solution procedure is presented to find optimal or near optimal operating-policy variables. Solutions of the model to a large number of test examples show that the model outperforms other existing models in the literature without sacrificing the computation time. Tested against the lower bounds on the optimal average annual variable cost obtained by removing some of the ordering costs, the solutions of the present model are found to be near optimal.     

Joint replenishment model with substitution

When products are coupled to the same cycle, the joint replenishment model (JRM) is used to determine optimal inventory levels, where the amount to order (for each item) is designed to minimize the joint holding and ordering costs based on a given demand. JRM studies assume that there is no substitution between items. However, this assumption is unrealistic in some settings where substitution cannot be ignored. This paper combines the separate works on substitution and joint replenishment and proposes a solution procedure for solving the joint replenishment model with substitution (JRMS) for two products within the framework of the classical economic order quantity model. We determine the optimal order quantities for each product taking into consideration substitution between them so that demand is partially met and the total cost associated with the delivery, holding, and shortage of the products is minimized. We also provide an extensive scenario analysis and draw insights. In particular, we shed some light on the role of substitution in reducing the fixed cost. We show that JRMS can result in substantial cost savings compared to the ordinary JRM.     

A periodic-review inventory control policy for a two-level supply chain with multiple retailers and stochastic demand

We consider a time-based inventory control policy for a two-level supply chain with one warehouse and multiple retailers in this paper. Let the warehouse order in a fixed base replenishment interval. The retailers are required to order in intervals that are integer-ratio multiples of the base replenishment interval at the warehouse. The warehouse and the retailers each adopt an order-up-to policy, i.e. order the needed stock at a review point to raise the inventory position to a fixed order-up-to level. It is assumed that the retailers face independent Poisson demand processes and no transshipments between them are allowed. The contribution of the study is threefold. First, we assume that when facing a shortage the warehouse allocates the remaining stock to the retailers optimally to minimize system cost in the last minute before delivery and provide an approach to evaluate the exact system cost. Second, we characterize the structural properties and develop an exact optimal solution for the inventory control system. Finally, we demonstrate that the last minute optimal warehouse stock allocation rule we adopt dominates the virtual allocation rule in which warehouse stock is allocated to meet retailer demand on a first-come first-served basis with significant cost benefits. Moreover, the proposed time-based inventory control policy can perform equally well or better than the commonly used stock-based batch-ordering policy for distribution systems with multiple retailers.     

Coordinating ordering and pricing decisions in a two-stage distribution system with price-sensitive demand through short-term discounting

We consider a short-term discounting model in which the distributor offers a discounted price for the retailers’ orders placed at the beginning of its replenishment cycle, in a non-cooperative distribution system with one distributor and multiple retailers, each facing price-sensitive demand. We examine the value of the price discount strategy as a mechanism for the distributor to coordinate the retailers’ ordering and pricing decisions under two common types of demand, linear demand in price and constant elasticity demand in price. Our numerical study reveals that, in the presence of homogeneous retailers (namely, retailers with identical demand rates), the distributor’s profit improvement due to coordination generally decreases as the number of retailers or the inventory holding cost rate increases, but increases as price elasticity increases. Although an increase in the inventory holding cost rate has a negative effect on the distributor’s profit, it may have a positive effect on the retailers’ profits. We further find that with heterogeneous retailers (namely, retailers with different demand rates), offering a discounted price under linear demand benefits the distributor when both the inventory holding cost rate and the variation in demand are either small or large. This cross effect, however, is absent under constant elasticity demand.