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。     

需求随价格变化的具有折扣的易变质物品的库存模型

本文研究了在需求随价格变化及物品易变质的条件下，当供应商给予数量折扣时的库存问题。证明了当供应商给予数量折扣时，零售商的需求量是增大的，并给出了供应商给予数量折扣时零售商的订货量和订货周期的计算方法。对物品变质率和需求价格敏感系数对零售商的订货量、订货周期、出售价格和单位时间利润的影响进行了数值分析，并给出了数值算例。     

非对称信息下供应商-零售商供应链的批量折扣决策

在供应链管理的文献中,许多工作研究供应商如何使用激励手段,如数量折扣,去影响零售商的订货行为以增加供应商的利润(与整个供应链的利润).多种形式的激励策略模型已有许多,但通常有一个关键的假设,即,供应商关于零售商的成本结构具有完全信息.本文研究了在非对称信息下供应商的最优数量折扣决策问题,得到了最优策略,并与完全信息的情形进行了比较.     

不同情形下供应链优化决策模型的比较分析

本文提出三种不同情形（制造商与零售商追求各自利润最大化，并且没有价格折扣策略；制造商与零售商共同追求总利润最大化，不实施价格折扣策略；制造商与零售商共同追求总利润最大化，并实施价格折扣策略）下供应链价格和库存补充策略的优化决策模型，并通过具体数例进行比较分析，结果表明，供应链合作并实施价格折扣策略时的供应链总利润最高，而供应链双方利润分配系数的变化对基于供应链总利润最大化的供应链优化决策没有影响．     

模糊随机需求报童问题的Stackelberg-Nash均衡策略

针对模糊随机需求下的分布控制型报童问题,建立了无数量折扣和有数量折扣情况下的利润最大化两层规划模型,并结合模糊随机模拟技术和遗传算法设计了模型求解的混合智能算法.解决了上层制造商制定包括折扣区间和折扣价格的最优数量折扣策略,以及下层多零售商确定各自的最优订货量的Stackelberg-Nash均衡策略问题.     

可替代产品环境下基于数量折扣的供应链协调研究

研究一个供应商和一个零售商基于数量折扣的两种可替代产品供应链协调问题,建立以供应商为主导的可替代产品数量折扣Stackelberg博弈模型,并将数量折扣模型与一体化和非一体化情形作对比,分析产品折扣率和替代率的变化对供应链的影响.研究结果表明虽然整个供应链利润随折扣率和产品可替代程度的增加而增加,但只是增加了处于主导地位供应商的利润,降低了零售商的利润;在实际运营中,供应商需要考虑销售返利或其它转移支付手段将利润一部分转移给零售商来实现基于数量折扣的供应链协调.     

收益共享的寄售契约下供应商生产成本谎报行为分析

在收益共享寄售契约下的两级供应链中,供应商向零售商报告其生产成本;零售商根据供应商报告的生产成本,决定零售商的收益分配比例;供应商决定零售价格和生产数量,并且保持产品的所有权.由于信息不对称,供应商可能谎报其生产成本.作者应用博弈论分析了供应商谎报行为对供应链及其成员决策及绩效的影响.利用解析的方法得出一些理论结果:零售价格在信息对称时小于生产成本信息不对称时;订货数量在信息对称时大于生产成本信息不对称时;零售商的利润分配比例在信息对称时大于生产成本信息不对称时.供应商的谎报行为使其自身利润增加,使零售商和供应链的利润减少.     

异质性生鲜农产品供应链的差别定价与协调策略

在单一供应商生产的两种产品存在替代性,需求受自身价格、新鲜度以及替代品价格共同影响的条件下,研究了受数量损耗影响的生鲜农产品供应链的定价策略及协调问题.比较分析了集中式与分散式决策下的最优策略,讨论了竞争替代系数以及可控的新鲜度和数量损耗率对最优决策的影响,进而给出了继续提升系统总利润的决策空间和顾客共赢的决策范围.并设计了"利润共享契约"对供应链进行协调,当契约参数在一定范围内变化时,该契约能实现供应商、零售商和顾客三方的共赢,供应商也拥有继续提升系统总利润的动力.     

多因素干扰下的供应链最优定价与订货决策

在信息不对称条件下,市场需求、价格和风险厌恶等因素同时干扰时,构建数量折扣契约的供应链博弈模型,寻找其实现供应链协调的内在约束条件。根据显示原理,构建信息不对称条件下多因素干扰的CVaR模型并求解,然后用算例仿真,结果表明:供应商隐瞒生产成本信息会带来额外收益,但给零售商造成额外损失。价格随机与零售商厌恶风险的耦合作用是导致供应链上各决策变量发生分岔现象的内因,与信息是否对称无关。但信息不对称会损害供应链系统的稳定性。在分岔突变区域内供应链失调,在区域之外供应链协调。零售商风险中性的态度和提高信息透明度有利于提高整个供应链的绩效。     

指数函数需求下供应链公平偏好信息动态演进研究

在指数函数需求下对零售商公平偏好信息动态演进进行了研究,并与线性需求条件下的研究结论进行了对比分析。研究发现:两种需求条件下可得到相同的结论,如批发价格和零售价格对公平偏好的敏感性分析,批发价格契约不能协调供应链,但却能缓减"双重边际效应"等.同时还发现:两种需求条件下可得到不同的结论,如当零售商为公平偏好类型且信息非对称时,零售商效用、供应链效用在指数函数下随自身公平偏好强度递增而在线性需求函数下随自身公平偏好强度递减等.需求函数的形式会影响供应链中的利润分配,在指数函数需求条件下,零售商利润肯定不比供应商少且只要零售商向供应商传递公平偏好信号,那么零售商就一定能够超过供应商利润,且超过部分随公平偏好度递增.     

A fuzzy newsvendor approach to supply chain coordination

In the absence of a clear command and control structure, a key challenge in supply chain management is the coordination and alignment of supply chain members who pursue divergent and often conflicting goals. The newsvendor model is typically used as a framework to quantify the cost of misalignment and to assess the impact of various coordination initiatives. The application of the newsvendor framework, however, requires the specification of some probability distribution for the sources of uncertainty, and in particular, for the market demand. The specification of an adequate demand distribution becomes difficult in the absence of statistical data. We therefore consider a fuzzy approach to the newsvendor problem. We use several fuzzy parameters in the model for the demand, the wholesale price, and the market sales price. We solve the fuzzy newsvendor problem to study three coordination policies: quantity discounts, profit sharing, and buyback. For each coordination policy, the optimal order quantity of the retailer is computed. The possible profits of the members in the supply chain are calculated with minimum sharing of private information. We further extend the fuzzy newsvendor model to a setting with a single manufacturer and multiple retailers under the assumption of ample capacity for the manufacturer. Detailed numerical examples are also provided.     

供应提前期和需求不确定下库存系统的随机比较

本文研究供应提前期和需求不确定下包含最小化成本和最大化利润的一致化报童问题中随机比较实现的充分条件,并通过随机比较定量刻画提前期和需求不确定性对库存系统决策和利润的影响。首先引入报童收益函数,给出其优化前后满足随机占优及拉普拉斯变换序的充分条件。进一步,在周期需求服从指数分布的情形下,定量刻画固定提前期与提前期服从几何分布两种情况的随机单调性。最后,将上述结论应用到报童模型中,得到提前期需求对一致化报童问题的随机单调性。     

Loss-averse newsvendor problem with supply risk

Modeling the manufacturer as a newsvendor, in this paper we study the ordering decisions of a loss-averse newsvendor with supply and demand uncertainties. Using the stylized newsvendor models, we analyse several key issues, including the effect of the newsvendor’s loss aversion, the effect of demand uncertainty, and the effect of supply uncertainty on the decision maker’s optimal decision under the procurement model, in which the decision maker only pays for the actual quantity received. Through our analysis, we find the following facts: the optimal order quantity decreases with respect to the degree of loss-aversion; the supply uncertainty induces the decision maker to order more than that in a deterministic environment; a stochastically larger demand always results in a larger order quantity and a larger expected utility; the optimal expected utility decreases in the demand volatility while the optimal order quantity may increase or decrease. Moreover, with numerical experiments, we demonstrate that the supply risk negatively affects the utility more than the demand risk does.     

Decision-making and the newsvendor problem: an experimental study

This paper investigates repetitive purchase decisions of perishable items in the face of uncertain demand (the newsvendor problem). The experimental design includes: high, or low profit levels; and uniform, or normal demand distributions. The results show that in all cases both learning and convergence occur and are effected by: (1) the mean demand; (2) the order-size of the maximal expected profit; and (3) the demand level of the immediately preceding round. In all cases of the experimental design, the purchase order converges to a value between the mean demand and the quantity for maximizing the expected profit.     

Channel coordination with manufacturer��s return policies within a newsvendor framework

The saliency of returns in today’s business world is unquestionable, in such items as toys, Christmas decorations, books, seasonal/fashion items and the like. This is largely due to the high economic benefits prevalent in some industries today and to the increasing opportunities for resale in secondary and global markets. This paper attempts to model the profitability of returns policy in presence of a secondary market, to a profit-maximizing manufacturer in a newsvendor framework. The returns policy applies both for the unsold merchandise left at the end of the selling season and the items returned by the unsatisfied customers within the specified time period. With a returns policy, the manufacturer shares the risks of demand uncertainty, in turn assuaged by the availability of secondary market. The manufacturer’s decision is to arrive at an optimal wholesale price and the returns policy, based on the retailer’s reaction on that offer. The retailer in turn optimizes the retail price and the order quantity to meet a price-dependent uncertain demand. This set of optimal policies has then been contrasted to that obtained from maximizing the combined profit of the manufacturer and of the retailer. The key question in the comparison has been clearly answered. The total combined profit that coordinates the policies of both channels exceeds that of the sum of the profits obtained independently.     

Robust multi-market newsvendor models with interval demand data

We present a robust model for determining the optimal order quantity and market selection for short-life-cycle products in a single period, newsvendor setting. Due to limited information about demand distribution in particular for short-life-cycle products, stochastic modeling approaches may not be suitable. We propose the minimax regret multi-market newsvendor model, where the demands are only known to be bounded within some given interval. In the basic version of the problem, a linear time solution method is developed. For the capacitated case, we establish some structural results to reduce the problem size, and then propose an approximation solution algorithm based on integer programming. Finally, we compare the performance of the proposed minimax regret model against the typical average-case and worst-case models. Our test results demonstrate that the proposed minimax regret model outperformed the average-case and worst-case models in terms of risk-related criteria and mean profit, respectively.     

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 practical inventory control policy using operational statistics

Consider the newsvendor inventory control problem with an ambiguous demand. The traditional approach of separating the parameter estimation and the maximization of the expected profit leads to a suboptimal inventory policy. Operational statistics, introduced in this paper, provides a better solution by integrating the estimation and the optimization tasks.     

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.