三层供应链上需求信息不对称下Newsboy型协作问题

本文主要研究单产品在单周期内由供应商、制造商、零售商组成的三层供应链上的协作订购问题,即在随机需求下供应商、制造商、零售商以利润最大化为目的的最优协作订购问题。在需求信息不对称下,零售商充分了解需求信息。在协作订购时面临四种策略,给出了在这四种策略下的四种利润模型及零售商在这四种策略下的最优订购量并比较它们的大小,最后通过需求服从正态分布的实例验证了供应商一制造商一零售商在采用数量折扣和返回措施三者完全合作时供应链上的利润最大。     

可追加订购的报童问题

研究带有追加 (两次 )订购的报童模型 ,分析了此模型与经典 (一次订购 )报童模型的收益关系 ,服务水平评价 ,订购量与需求均值、方差、价格等的灵敏度及发现了在适当的条件下 ,最大追加订购量 M的最优解存在 ,且给出了求解的方法 .     

提前期需求为模糊随机条件下的连续库存补货策略

考虑提前期内需求为模糊随机变量且提前期为可缩短情形下,建立由购买商和供应商所组成的简单供应链连续库存补货策略优化模型,其中订单量、再订货点和提前期为决策变量.首先推导出模糊随机需求条件下购买商和供应链的成本函数,然后,进一步考虑总需求为三角模糊数,推导出供应商、购买商和供应链的模糊成本函数.在此基础上分别从购买商成本最小和供应链成本最小角度对模型进行求解,结合具体算例对模型进行应用分析和比较分析,结果表明模型具有有效性和实用性,并得出如下结论:从购买商本身角度考虑订购策略所产生的供应链成本总是大于从供应链整体角度考虑订货策略所产生的供应链成本,同时从购买商本身角度考虑订货策略所产生的最优订购量、购买商成本低于从供应链整体角度考虑订货策略所产生的最优订购量、购买商成本.     

随机局部弹性及在库存管理中的应用

提出随机局部弹性的概念，讨论了相应的运算法则，研究了不允许缺货的存贮模型中，总费用对采购量与采购周期的局部弹性。给出了总费用联合概率密度的一般表达式。通过实例说明，当采购量与采购周期的分布特性已知时，总费用的弹性变化范围就完全被确定。     

基于差价补偿策略的斯塔克尔伯格博弈协调优化

以智能产品为研究对象,建立了差价补偿策略下制造商与销售商的博弈模型,分别通过纳什均衡博弈和斯塔克尔伯格博弈协调优化对制造商和销售商的决策行为进行探讨,得到了Nash均衡下制造商与销售商之间交易策略,讨论了斯塔克尔伯格博弈下制造商的最优订购、最优补偿系数和销售商的订购量之间关系,提出了求解在给定补偿系数下斯塔克尔伯格博弈协调优化的近似最优批发价与最优订购量的算法。通过数值实验表明,制造商占优势地位时,差价补偿策略能实现整体供应链的协调优化,提高销售商的订购量以及制造商和销售商的利润,说明差价补偿策略可以有效地改善零供关系。     

两类供应风险下装配商的最优订购策略

针对两类供应风险(不确定产能与随机产出率)下装配制造商的零部件订购决策这一难题,运用随机非线性规划方法,以装配商期望利润最大化为目标,建立零部件订购决策的多维优化模型,刻画了确定需求下的最优订购量,并对其进行了灵敏性分析。最后,通过数值算例验证了模型结论并进一步探讨不同类供应风险的影响,为装配商的零部件订购决策和风险管理提供有益的管理启示。     

损耗性物品信用交易下的斯坦博格库存模型

目前众多的信用交易模型是在供应商给定的信用交易期限条件下,零售商确定最优订购数量或订购周期,而很少考虑供应商信用交易策略的制定问题。本文针对损耗性物品,在最终需求为价格的线性函数条件下,利用斯坦博格博弈模型给出了信用交易下供应商信用交易策略的制定和零售商的最优订购决策,最后通过算例对模型进行了验证。     

基于M-CVaR和生产资金约束的供应链协调研究

本文针对供应商面临生产资金约束的情况,在需求随机条件下研究了由一个风险中性零售商和一个具有风险偏好的供应商组成的二级供应链的协调问题。文章在零售商享有批发价折扣的提前支付和供应商银行信贷两种融资方式下,分别建立了零售商的最优决策模型以及基于M-CVaR测度工具的供应链整体订购决策模型,并给出了采用两种不同融资模式时零售商和供应链整体的最优订购量以及供应链的协调条件,分析了供应商的风险偏好对供应链整体最优决策及协调条件的影响。最后通过算例验证了文章的主要结论。研究表明,当提前支付价格折扣大于临界值时,零售商会选择提前支付货款;提前支付模式下供应链整体的最优订购量大于银行信贷模式;随着供应商的风险偏好由风险规避向风险喜好转变,供应链整体的最优订购量逐渐增大。     

机会损失最小化报童模型中的订购决策研究

结合条件风险值(conditional value-at-risk,CVaR)准则对机会损失最小化报童模型中零售商的订购决策进行研究.研究结果表明:当订购过量损失大于订购不足损失时,零售商基于CVaR机会损失最小化的订购量小于期望机会损失最小化的订购量,且随着零售商对风险厌恶程度的增加而减少;反之,当订购过量损失小于订购不足损失时,零售商基于CVaR机会损失最小化的订购量大于期望机会损失最小化的订购量,且随着零售商对风险厌恶程度的增加而增加;随着零售商对风险规避程度的增加,零售商基于CVaR机会损失最小化的订购量所对应的期望利润和期望机会损失分别减少和增加,即低风险意味着低收益,高收益伴随着高风险.     

一类最优EOQ模型的进一步扩展

对一类经济批量订购模型作如下进一步扩展:第一,允许短缺,短缺量部分拖后供给,且短缺期间损失率与实际缺货量成正比;第二,订购费用是可变的,且线性依赖于订购量.在此假定下,研究了有限计划时间水平及常数变质率下,部分短缺量拖后的变质性物品多阶段库存问题,给出了寻找最优订购策略的算法,证明了所给最优策略的存在唯一性及在该策略下费用函数取得最小值.最后给出应用实例.     

整批间隔进货的存储量控制模型与随机局部弹性

利用作者于文[1，2]引入的随机弹性理论，研究了整批间隔进货并不允许缺货的随机存储模型中，一个采购周期内的总费用对最高存储量的弹性．给出了总费用弹性概率密度函数的一般表达式．进一步给出了存在多种需求物资的随机存储模型中总费用对单个物资采购量的弹性分布函数和概率密度函数，讨论了随着采购量的随机变化，总费用的弹性变化规律和变化范围．通过实例研究了当最高库存量的分布特性已知且采购量服从某一分布时，总费用的弹性变化范围及在该变化范围的可信度．     

Effect of the server capacity distribution on the optimal control of a bulk service queueing system

In this paper the optimal control of a single-channel bulk service queueing system with random server capacity is investigated. Given an accumulation level r, the server stops processing new customers whenever the queue falls below r and resumes service when the queue reaches level r again. Server capacity becomes random following an idle period. A quick search procedure is designed to determine the value of r that yields the minimum expected total cost per unit of time. The effect of the server capacity distribution on the optimal control is then studied. Finally, a sensitivity analysis is conducted in order to assess the extent to which our results are valid.     

The stochastic EOQ model with random sales price

The article deals with a stochastic economic order quantity (EOQ) model over a finite time horizon where uniform demand over the replenishment period is price dependent. The selling price is assumed to be a random variable that follows a probability density function. As demand is probabilistic, stock out situation may occur. Based on the partial backlogging and lost sale cases during stock out period, the author develops the criterion for the optimal solution for the replenishment size such that the integrated expected profit is maximized. Moreover, the article suggests a new function regarding price dependent demand. Finally, numerical examples and its sensitivity analysis of key parameters are given to illustrate the proposed model.     

On the convexity for the expected total cost per unit time of the EPQ model with scrap,rework and stochastic machine breakdown

This study explores the economic production quantity model with scrap, rework and stochastic machine breakdown. The main purpose of this paper is twofold:(P1) This paper will adopt the rigorous methods of mathematics to demonstrate that the expected total cost per unit time is convex on all positive numbers to improve the conditional convexity in Theorem 1 of Chiu et al. (2010) [7].(P2) This paper gives the concrete proof to provide bounds for the optimal production run time to remove the logical shortcomings of mathematics presented in proof of Theorem 2 of Chiu et al. (2010) [7].     

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.     

随机需求弹性及在经济分析中的应用

引入随机弹性的概念及随机弹性的相关性质，进而给出随机需求弹性．利用随机需求弹性分析了当消费群体的收入为随机变量时，其收入对需求量的变化和影响．给出了当收入服从某种分布时，需求量的弹性分布．     

Economic order quantity models with nonlinear holding costs

We consider a generalization of the classical Economic Order Quantity Model. The traditional parameters of unit cost, selling price, demand rate and set-up cost are constant but the holding cost per unit is a non-linear function of the length of time the item is held in stock. The application is to any inventory system where the value of the item decreases non-linearily the longer it is held in stock. For the case of deterministic demands we present the cost formula and the optimal order quantity for both finite and infinite horizons. For the case of stochastic demands the cost function is examined and the optimal order amount is presented. Computational results are presented indicating the effect of the non-linearity in holding costs.     

Random fuzzy EOQ model with imperfect quality items

This paper investigates an economic order quantity (EOQ) problem with imperfect quality items, where the percentage of imperfect quality items in each lot is characterized as a random fuzzy variable while the setup cost per lot, the holding cost of each unit item per day, and the inspection cost of each unit item are characterized as fuzzy variables, respectively. In order to maximize the expected long-run average profit, a random fuzzy EOQ model is constructed. Since it is almost impossible to find an analytic method to solve the proposed model, a particle swarm optimization (PSO) algorithm based on the random fuzzy simulation is designed. Finally, the effectiveness of the designed algorithm is illustrated by a numerical example.     

Modeling and analysis for determining optimal suppliers under stochastic lead times

The policy of simultaneously splitting replenishment orders among several suppliers has received considerable attention in the last few years and continues to attract the attention of researchers. In this paper, we develop a mathematical model which considers multiple-supplier single-item inventory systems. The item acquisition lead times of suppliers are random variables. Backorder is allowed and shortage cost is charged based on not only per unit in shortage but also per time unit. Continuous review (s,Q)$(s\text{,}Q)$ policy has been assumed. When the inventory level depletes to a reorder level, the total order is split among n suppliers. Since the suppliers have different characteristics, the quantity ordered to different suppliers may be different. The problem is to determine the reorder level and quantity ordered to each supplier so that the expected total cost per time unit, including ordering cost, procurement cost, inventory holding cost, and shortage cost, is minimized. We also conduct extensive numerical experiments to show the advantages of our model compared with the models in the literature. According to our extensive experiments, the model developed in this paper is the best model in the literature which considers order splitting for n-supplier inventory systems since it is the nearest model to the real inventory system.