合约决策条件下的一种二层报童问题模型

考虑到顾客需求和市场价格具有高度的不确定性，供应商和零售商为了回避风险而达到最大的期望利润，双方通常可以采用签订合约的方式来进行决策。为此，我们建立了以供应商为领导层、零售商为从属层的具有合约决策的一个二层报童模型。供应商和零售商可以依据该模型的最优解通过谈判协商确定合约决策变量值以获取较高的期望利润。     

具有单向转载的Newsboy型产品订货决策的博弈模型

研究了允许单向横向转载的Newsboy型产品的订货决策问题。以两个Newsboy型零售商为研究对象,在允许单向横向转载存在的前提下,构建了以二者期望利润最大化为目标的非合作博弈模型,讨论了模型存在纳什均衡解的条件并证明了解的存在性与唯一性,给出了均衡解的解析表达形式,进一步分析了转载价格对均衡的影响。最后的算例分析则从期望利润、均衡订货和转载价格三个方面验证了横向转载策略的优势。研究表明:(1)与传统报童模型相比,横向转载策略提高了零售商的期望利润;(2)转载价格显著影响横向转载策略下零售商的订货决策。     

多个过度自信零售商最优订货策略研究

研究在竞争环境下过度自信零售商对市场需求的信念存在偏差时的订货决策问题.在仅知市场需求的均值和支集的情况下,应用最大绝对后悔最小化准则,建立多个过度自信零售商的鲁棒订货模型.证明了具有多个零售商竞争的报童博弈的鲁棒优化Nash均衡解的存在性,并导出了最优决策的封闭表达式.讨论过度自信行为对零售商最优订货量和期望利润的影响.数值分析结果表明:在最小化最大绝对后悔值准则下,过度自信零售商获得的实际期望利润要低于其获得的信念期望利润;在两个零售商的非对称博弈情形,过度自信零售商获得的实际期望利润要高于完全理性零售商获得的期望利润,并且每个零售商获得的实际期望利润还随其竞争对手的过度自信程度的增加而增加.过度自信可以使那些在库存可用性上相互竞争的零售商获益.     

需求不确定性对闭环供应链系统决策的影响分析

在由一个制造商与一个销售商组成的闭环供应链系统中,构建了市场需求不确定环境下废旧产品回收率为外生变量和零售商决策变量两种情形的闭环供应链系统决策模型,并通过数值仿真得到了各模型供应链成员的最优定价和订货策略以及最终利润,进一步分析了两种情形下市场需求不确定性对零售商、制造商决策行为及利润的影响,最后对两种情形进行了对比分析.     

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.     

需求不确定的供应链两阶段订货模型

销售商如何在不确定需求的市场环境下根据制造商提供的订货条件进行合理订货是供应链管理的一个核心问题。本文利用信号博弈的原理从销售商的角度研究在不确定需求且传统需求预测方法失效的情况下，允许调整订货量的短生命周期产品两阶段订货模型，得到了在两次订货条件下销售商应该采取的最优订货量与调整策略以及制造商对契约灵活性限制的成本函数。     

随机需求下单供应商与多零售商的生产—库存—运输联合优化模型

考虑随机需求下单供应商和多零售商的生产-库存-运输联合优化问题.在独立决策时,各零售商独立决策其最优订货量和最优订货点,供应商根据各零售商的决策来为之配送.在联合决策时,由供应商统一决策各零售商的送货量和送货时间,并基于此建立单供应商与多零售商的生产-库存-运输优化模型,利用粒子群算法和模拟退火算法相结合的两阶段算法求出最优送货量、最优运输路径和最大期望总利润.然后采用收入共享契约将增加的利润合理分配给供应商和各零售商,使各方利润都得到增加,从而促使各方愿意合作.最后,通过数值算例验证了联合优化模型优于独立决策模型.     

基于古诺博弈策略的报童问题的模型及分析

通过建立和分析基于古诺博弈策略的报童问题的数学模型,寻求两个销售商有重叠销售区域时的竞争价格策略优化方法.模型的主要特点是:基于蜂窝理论刻画每个销售商的营销区域呈正六边形,分析了相邻销售商有重叠销售区域时,如何确定最优竞争价格策略,保证其利润最大;其次,该模型把需求量看成价格的函数,将消费者与销售商的距离看成是影响实际消费行为的重要因素纳入到消费者密度函数.     

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。     

模糊随机需求下多产品报童问题的均衡策略

针对模糊随机需求下单制造商多零售商的分布控制型多产品报童问题, 建立了含资金约束的期望利润最大化两层规划模型.结合模糊随机模拟技术与遗传算法, 设计了求解模型的混合智能算法.该算法不仅可获得上层制造商的最优折扣批发价及下层零售商的最优订购量,亦可求得该折扣形式的起始折扣点(折扣区间).算例分析表明,当制造商采取最优数量折扣策略时:1)促使零售商订货量增加至资金约束上限;2)部分产品订货量可达模糊随机市场需求的最大可能值:3)零售商和制造商的利润均增加.     

退货情形下基于替代率的两产品联合订货决策研究

研究了一类在产品订货模型中考虑客户退货和产品间替代的两产品联合最优订货决策问题.假定客户以一概率退回其所购产品,退货产品经修复后可重新在市场上进行销售,销售期末未售出的商品只能在二级市场上降价处理,且不同产品间存在替代关系,销售商以自身利润最大化为目标确定两产品的订货量,得到其最优订货量及一些性质.研究结果表明:在允许退货的背景下,替代策略的采用将会进一步提高销售商利润.     

Postponed two-pricing and ordering opportunity for selling a single season inventoried product

Postponement strategies are becoming increasingly important in light of a global trend in which products’ life-cycles are decreasing, such that even products that are not traditionally considered seasonal become “obsolete” within a short period of time (e.g., electronic devices, new cars). Our work addresses postponed-pricing and ordering decisions for a retailer who sells a newsvendor-type inventoried product, in a selling season that is divided into two sub-periods. The division of the selling season enables the retailer to on-line adjust her decisions when faced with a scenario (one that is highly prevalent in reality) in which potential demand changes (increases or decreases) following consumers’ experiences of the product in early stages of the selling season. We assume that the retailer has two opportunities for receiving shipments: prior to the first sub-period and prior to the second one. The retailer determines each order quantity (base-stock level) on the basis of the demand distribution for the corresponding sub-period. In each sub-period, after observing additional market signals, the retailer determines the price of the product for that sub-period. With the aid of a stochastic programming approach, we develop optimization problems and solution methods in order to obtain pricing and ordering decisions that maximize the expected profit of the retailer. We present an extensive numerical example that compares the suggested strategy to three alternative strategies, and conclude that price postponement and responsiveness to demand changes can each reduce leftovers and lost sales as well as substantially increase expected profit.     

Coordinating order quantity decisions in the supply chain contract under random demand

In this paper, we are concerned with the coordinating quantity decision problem in a supply chain contract. The supply chain contract is composed of one manufacturer and one retailer to meet the random demand of a single product with a short lifecycle. Our analysis show that the retailer expects to obtain higher profit under proper ordering policies, which can also maximize the expected profit of the supply chain. The manufacturer may induce the retailer to order the coordinated quantity by adjusting the unit return price. As a result, the supply chain is expected to achieve the optimal expected profit.     

Channel coordination under two-level trade credits and demand uncertainty

This study considers a decentralized supply chain where a retailer has an opportunity to order a product from a supplier prior to the sales season to satisfy uncertain demand. The retailer provides trade credit to end customers and makes credit period and order quantity decisions to maximize profits. The end demand is both random and credit period-dependent. On the basis of the newsvendor model, this paper focuses on channel coordination when a retailer provides trade credit to end customers. When the supplier also provides trade credit to the retailer, we show that the traditional trade credit contract cannot coordinate the channel. Four composite contracts based on trade credit (trade credit cost sharing with buy back or quantity flexibility; modified trade credit with buy back or quantity flexibility) are provided to induce the retailer to make decisions while optimizing the channel profit. This paper shows that the retailer provides a longer credit period to its customers and orders a larger quantity from the supplier under the composite contracts. With these contracts, the profit sharing between both parties depends on the wholesale price (Pareto improvement) for the fixed retail price and the purchasing cost.     

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.     

Jointly pricing and ordering for a multi-product multi-constraint newsvendor problem with supplier quantity discounts

We present an extension to the multi-product newsvendor problem by incorporating the retailer’s pricing decision as well as considering supplier quantity discount. The objective is to maximize the expected profit of the retailer through jointly determining the ordering quantities and selling prices for the products, subject to multiple capacity constraints. We formulate the problem as a Generalized Disjunctive Programming (GDP) model and develop a Lagrangian heuristic approach for its solution. Randomly produced instances involving up to 1000 products are used to test the proposed approach. Computational results show that the Lagrangian heuristic approach can present very good solutions to all instances in reasonable time.     

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.     

Effect of declining selling price: profit analysis for a single period inventory model with stochastic demand and lead time

In this paper, considering the empirical trend for sales and price of fashion apparels as prototype, optimal ordering policy for a single period stochastic inventory model is investigated. The impact of the presence of random lead time and declining selling price on the profitability of the retailer is explored. Existence of unique optimal solutions for net profit functions is proved. Numerical examples are presented to illustrate the method of identifying profitable levels of inventory holding and penalty costs. Percentage profit per unit investment in inventory is obtained in order to assist managers in taking business decisions, specifically to the extent of whether or not to take up a particular business under known constraints. It is demonstrated that the optimal inventory policy in the absence of price decline and lead time differs considerably from that when lead time and price decline are simultaneously considered.     

零售商主导的模糊供应链博弈——考虑销售努力的情形

以包含一个制造商与一个零售商的两级供应链为研究对象,考虑零售商居于主导地位并付出销售努力时供应链各成员的决策。结合经济环境的不确定性,将市场需求函数和制造商的制造成本、零售商的经营成本视为模糊变量;运用斯塔克尔伯格模型刻画零售商和制造商之间的博弈过程,并引入期望值模型、机会约束模型来解决最优决策问题;通过一个数值算例证明了供应链博弈模型的有效性。研究表明,在均衡结果中,考虑到零售商所承担的销售努力成本,其总体期望值利润相比于制造商而言偏低,但单位产品边际利润较高。原因在于,零售商的主导地位使其不仅通过销售努力提高产品销量,提高了供应链的整体利润,同时也能够采用压低批发价格的方式,使自身在供应链中获取更多收益。     

Modeling a multi-attribute utility newsvendor with partial backlogging

Traditional newsvendor models usually focus on single profit maximization or cost minimization approaches. However, making a monetary estimate of the consequences of lost sales as a result of shortages is often a difficult task for many practitioners. Besides, there is still a lack of an explicit account of decision-making judgments on the multiple consequences of making decisions with regard to order quantities. In order to deal with this problem, this paper presents a multi-attribute utility model for the newsvendor problem with regard to profit, the impacts of service level on corporate image and on customers’ goodwill, and the impact on the environment arising from the disposal of unsold products. Demand is partially backlogged according to a decreasing exponential function of the waiting time. The fundamental principles and limitations related to the application of the model built are also discussed.