具有多元马氏需求的易变质多产品的EOQ模型

本文研究一类新的易变质多产品库存控制策略,即具有多元马氏需求特征的多产品的最优(Q,T,?t)策略,该策略综合考虑了市场需求在不同产品之间具有马氏转移特征和变质率因素。论文首先建立了多产品多周期的多元马尔可夫需求预测模型,并通过该模型确定了各种产品在订货周期内的需求之间的关系。同时,在该关系的理论基础上,进一步给出了多产品多周期库存的最优(Q,T,?t)策略,进而结合算例给出模型的最优策略的数值解。     

带有马尔可夫竞争因子的多产品报童模型

在竞争的环境下考虑多产品报童问题。为了刻画多产品间的竞争关系，本文利用马尔可夫链构建多产品的需求转移模型，并根据模型的转移概率矩阵提出马氏竞争因子和综合竞争力等核心概念，进而结合卷积公式和雅可比行列式，将竞争因子的概念纳入经典报童模型的框架，构建了带有马氏竞争因子的多产品报童模型，同时在该模型的理论基础上给出了新的决策机制。模型的数据实验表明：竞争因子对多产品库存系统的最优订购策略具有重要的影响，关于产品的综合竞争力为单调递增函数；将竞争因子纳入多产品库存系统的决策机制，可进一步拓展报童模型在实际应用领域中的适应性以及提高库存系统的优化与控制的效用。     

带有能力约束的多元马氏需求报童模型

在随机需求环境下考虑带有能力约束的多产品报童问题.为了对多产品的需求进行预测,并度量其需求间的关系,本文首先建立了多元马氏需求模型.其次,在该模型的理论基础上,提出了带有能力约束的多元马氏需求报童模型,进而给出多产品的最优订购策略解.最后,利用期望需求状态的概率值及其截尾概率分析了模型最优解的性质.模型的结论表明,在能力约束的条件下,最优订购量关于左截尾概率单调递减,关于右截尾概率单调递增,而期望需求状态的概率值对最优订购量具有双重的特殊影响.     

服务多类需求串行供应链的最优控制策略

研究由一系列生产环节采用串行方式组成多级供应链的最优控制策略.在此供应链中,原材料经过各级生产环节顺序加工形成最终产品.各级生产环节的加工时间服从随机分布.对最终产品存在多类随机需求.在每个时刻,管理者需要决定:1)是否该启动某个生产环节的生产;2)当有需求到达时,是否该满足此需求.管理者期望系统运行的总期望折扣成本最小.构造了该系统的马尔可夫决策模型并深入研究了其最优控制策略及其动态协同特性.在生产策略方面,证明系统的最优生产策略就是对各级生产环节采用动态的基本库存策略.该策略的动态协同特性主要体现在各级生产环节的最优基本库存水平受其他生产环节的库存水平影响.在产品分配方面,证明系统的最优分配策略是动态配给策略.该策略的动态协同特性主要体现在每类随机需求最优配给水平受各级生产环节的库存水平影响.     

爱尔朗型按订单装配系统最优生产——库存控制策略研究

本文研究具有复杂装配结构的爱尔朗型按订单装配(ATO)系统的组件生产与库存优化控制问题。系统涉及多种组件,一个最终产品和多类客户需求。在此系统中,各种组件的生产时间服从爱尔朗分布,各类客户的需求为泊松到达过程。针对不同客户需求类型:产品需求与独立组件需求且同为销售损失型,建立基于马尔可夫决策过程(MDP)的平均总成本模型,应用动态规划方法求解最优策略。仿真模拟方法实现最优策略,并通过数值实验分析多生产阶段和系统参数对最优策略的影响。研究结果表明,爱尔朗型生产时间ATO系统的最优策略为状态依赖型策略,即组件的生产与库存分配由动态基础库存水平值和动态库存配给水平值控制。对于任一组件,其基础库存水平值和库存配给水平值均随着生产阶段的增加而降低,且生产阶段对基础库存水平值和平均总成本的影响较显著。     

基于CPFR的多产品分销系统库存优化模型

本文中的分销系统由生产多种产品的多个制造商,一个地区分销中心DC,多个零售商所组成,系统采用基于CPFR来确定订货临界点,并且在假设DC和零售商都实行连续性盘点的(R,Q)库存控制策略,提前期为随机变量,零售商需求为泊松分布的前提下,以整个分销系统的库存成本最小化为目标函数,以DC和零售商的多产品服务水平为约束条件,通过确定最佳订货批量,建立了此多产品分销系统的库存优化模型,从而达到有效控制库存的目的.     

多类顾客环境下报童模型中库存分配策略研究

考虑一个报童模型中多类顾客的库存分配问题,将顾客按照他们愿意支付价格的高低划分为不同级别。零售商在销售期初决定产品订货量,并在销售期内决定接受或者拒绝不同顾客的需求,以最大化销售期内的期望总利润。将销售期分成大量足够小的时间单位,通过建立一个反向Bellman动态规划方程,以优化每个时间单位内的库存分配策略,并得到了零售商最优的期初订货量。通过与没有库存分配策略下零售商的期望利润进行比较,算例分析得出库存分配策略可以大幅提高零售商的利润。这主要是因为通过库存分配可以使得零售商从高端顾客中获取更多利润,同时能够减小期初的订货量,以节约采购成本和库存持有成本。     

航空公司机上周转品多基地库存优化模型

在民航业日益激烈的市场竞争环境下，航空公司对成本控制的精细化管理显得尤为重要。本文基于航空公司的实际背景，针对为旅客提供的机上周转品，建立了一个多基地库存系统的库存优化模型。该模型以系统的总库存成本最小为目标，在考虑需求、回收、调运、安全库存等因素下，决策一个订货周期内的订货及调运方案。基于最优解的分析，在成本参数满足一定条件下，可以得到系统最优的期初订货量；在此基础上，可以将该模型转化为一个网络流模型，参考最小费用最大流算法，设计了一个多项式求解算法来求解该网络流模型，进而得到各基地之间的最优调运量，并证明该算法的最优性；此外，根据期初订货量可行解的范围，设计了一个求解原库存模型的启发式算法。通过实例分析，验证了该模型与两种算法的有效性。     

考虑消费者参照效应与策略行为的多产品动态定价

在考虑客户同时表现出参照依赖和策略行为的场景下，本文构建了一个垄断厂商两阶段的多产品动态定价模型。该模型将易逝品的销售分为正常价格阶段和促销价格阶段，每个阶段又分为多期。客户分为短视型和策略型，其中策略型客户会根据两个阶段价格的差异和获得商品的概率，决定是在第一阶段和等到第二阶段购买商品。基于随机动态规划的结构属性和超模理论，得到了两个阶段稳态价格的解析解，并且证明最优价格路径是单调且随着初始参照价格变化而变化。最后，通过对两种产品的数值实验，分析了各种参数对最优稳态价格的影响。结果显示，零售商可以采取多产品联合定价策略，即基于商店水平的定价策略，并通过调整核心产品的比重来获得更高的利润。     

考虑顾客缺货反应的多产品两阶段JIT联合订货

为了解决多产品两阶段联合订货决策问题,综合考虑顾客缺货反应及资源限制对订货决策的影响,提出资源限制条件下考虑CRS的多产品两阶段JIT联合订货策略。在此基础上,以零售商收益最大化为目标,建立了多产品两阶段JIT联合订货决策模型,并从初始解生成和殖民地国家革命方式两方面设计了改进的帝国主义竞争算法。从Gruen调查报告中选取三种不同规模的算例验证了模型和算法的适用性和有效性。研究表明：本文提出的考虑顾客缺货反应的多产品两阶段JIT联合订货方法既可以提高零售商的总收益,也能提高顾客的服务水平;当单位库存资源机会收益相近时,同组产品间不会发生替代情况,而当同组产品间的单位库存资源机会收益差距较大,且高于其他产品组的单位库存资源机会收益时,则该产品组便会出现缺货和替代情况,且若该组缺货产品的剩余资源单位机会收益小于其他组产品的单位资源机会收益,则该产品的剩余资源便会转移给其他缺货产品。研究结论可为零售商多产品两阶段JIT联合订货决策提供有益的参考。     

Inventory Rationing for Multiple Class Demand under Continuous Review

We consider how a firm should ration inventory to multiple classes in a stochastic demand environment with partial, class‐dependent backlogging where the firm incurs a fixed setup cost when ordering from its supplier. We present an infinite‐horizon, average cost criterion Markov decision problem formulation for the case with zero lead times. We provide an algorithm that determines the optimal rationing policy, and show how to find the optimal base‐stock reorder policy. Numerical studies indicate that the optimal policy is similar to that given by the equivalent deterministic problem and relies on tracking both the current inventory and the rate that backorder costs are accumulating. Our study of the case of non‐zero lead time shows that a heuristic combining the optimal, zero lead time policy with an allocation policy based on a single‐period profit management problem is effective.     

一类供应链中多产品的订购策略及实证研究

本文针对变质产品供应链,建立了多产品的库存模型,分析了基于五种不同订购策略下总成本函数的性质,提出了多种变质商吕的近似最优订购策略.并且运用本文的理论,对南京市某花卉礼品公司2004年9月的鲜切花订购决策进行了实证分析.     

Optimal Ordering Policies for Inventory Problems With Dynamic Information Delays

Information delays exist when the most recent inventory information available to the Inventory Manager (IM) is dated. In other words, the IM observes only the inventory level that belongs to an earlier period. Such situations are not uncommon, and they arise when it takes a while to process the demand data and pass the results to the IM. We introduce dynamic information delays as a Markov process into the standard multiperiod stochastic inventory problem with backorders. We develop the concept of a reference inventory position. We show that this position along with the magnitude of the latest observed delay and the age of this observation are sufficient statistics for finding the optimal order quantities. Furthermore, we establish that the optimal ordering policy is of state‐dependent base‐stock type with respect to the reference inventory position (or state‐dependent (s, S) type if there is a fixed ordering cost). The optimal base stock and (s, S) levels depend on the magnitude of the latest observed delay and the age of this observation. Finally, we study the sensitivity of the optimal base stock and the optimal cost with respect to the sufficient statistics.     

供应链融资结构视角下的零售商订购策略研究

本文引入供应链融资结构因素，在传统库存管理模型基础上，研究零售商在面临随机市场需求情形下考虑股权和债权等融资方式的订购策略，建立允许零售商延期支付的最优订购模型，利用最优化理论与方法得到了该模型的最优解，证明了最优解的存在性和唯一性，并分析了债权融资比例、价格成本比例系数、销售价格、订货周期、回购价格、进货价格、缺货成本、库存成本、以及融资利率等因素对最优解的影响。进一步，通过数值示例深入探讨具体市场环境下零售商的最优订购量，并进行了敏感性分析。研究发现，债权融资比例、价格成本比例系数、进货价格、订购周期、库存成本与零售商订购量存在负相关关系；缺货成本、回购价格、销售价格与零售商订购量正相关。相关研究结论可以为零售商订购行为提供科学指导，并为其库存管理提供重要决策依据。     

Unsold Versus Unbought Commitment: Minimum Total Commitment Contracts with Nonzero Setup Costs

We study a minimum total commitment (MTC) contract embedded in a finite‐horizon periodic‐review inventory system. Under this contract, the buyer commits to purchase a minimum quantity of a single product from the supplier over the entire planning horizon. We consider nonstationary demand and per‐unit cost, discount factor, and nonzero setup cost. Because the formulations used in existing literature are unable to handle our setting, we develop a new formulation based on a state transformation technique using unsold commitment instead of unbought commitment as state variable. We first revisit the zero setup cost case and show that the optimal ordering policy is an unsold‐commitment‐dependent base‐stock policy. We also provide a simpler proof of the optimality of the dual base‐stock policy. We then study the nonzero setup cost case and prove a new result, that the optimal solution is an unsold‐commitment‐dependent (s, S) policy. We further propose two heuristic policies, which numerical tests show to perform very well. We also discuss two extensions to show the generality of our method's effectiveness. Finally, we use our results to examine the effect of different contract terms such as duration, lead time, and commitment on buyer's cost. We also compare total supply chain profits under periodic commitment, MTC, and no commitment.     

Analysis of an EOQ inventory model with partial backordering and non-linear unit holding cost

In this paper, an economic order quantity inventory model is analyzed, considering that the unit cumulative holding cost has two significant components: a fixed cost which represents the cost of accommodating the item in the warehouse and a variable cost given by a potential function of the length of time over which the item is held in stock. Shortages are allowed and, during the stockout period, only a fraction of demand is partially backordered. The backordering cost includes a fixed cost and a cost linearly dependent on the length of time for which backorder exists. A solution procedure is developed for determining the optimal inventory policy. Moreover, to illustrate the effects of some parameters on the optimal policy and the minimum total inventory cost, a numerical study is developed.     

Optimal Inventory Control with Retail Pre‐Packs

A pre‐pack is a collection of items used in retail distribution. By grouping multiple units of one or more stock keeping units (SKU), distribution and handling costs can be reduced; however, ordering flexibility at the retail outlet is limited. This paper studies an inventory system at a retail level where both pre‐packs and individual items (at additional handling cost) can be ordered. For a single‐SKU, single‐period problem, we show that the optimal policy is to order into a “band” with as few individual units as possible. For the multi‐period problem with modular demand, the band policy is still optimal, and the steady‐state distribution of the target inventory position possesses a semi‐uniform structure, which greatly facilitates the computation of optimal policies and approximations under general demand. For the multi‐SKU case, the optimal policy has a generalized band structure. Our numerical results show that pre‐pack use is beneficial when facing stable and complementary demands, and substantial handling savings at the distribution center. The cost premium of using simple policies, such as strict base‐stock and batch‐ordering (pre‐packs only), can be substantial for medium parameter ranges.     

周期性需求下基于延迟订货的库存控制

本文在假设产品需求为周期性需求,订货周期为需求周期的整数倍,不能满足的需求在一定的时间间隔内允许缺货的前提下,提出一种确定性库存模型,并在此基础上,以满足单位时间内利润最大化为目标,研究并确定了优化订货批量、订货周期的时间间隔长度和缺货的时间长度的算法,最后给出算例,并验证了算法的可行性.     

On the benefits of operational flexibility in a distribution network with transshipment

We consider a centralized distribution network with multiple retailers who receive replenishment inventory to satisfy customer demand of the local markets. The operational flexibility of the network is defined as the opportunity that one retailer's excess inventory can be transferred to satisfy other retailers’ unmet customer demand due to stock-outs. A general modeling framework is developed to optimize retailers’ order quantities under any possible flexibility level of a stylized two-stage distribution network. We apply the framework to formulate and solve the transshipment problem of a distribution network with three retailers. Six typical flexibility levels are investigated to make the comparison study on the firm's profit performance under three ordering quantity policies: average demand, newsvendor order quantity, and optimal order quantity. We find that the operational flexibility and system optimization are complements to the firm's performance. The ordering policy with newsvendor ordering quantity can perform fairly well with moderate flexibility level when compared with the optimized ordering policy with full flexibility.