时变需求等量进货情形下集成供应链生产订货策略研究

构建了一个包含原料采购、生产和销售过程的集成供应链模型,研究了由原料、生产商和销售商产品构成的三层库存系统的生产订货问题。在有限的规划期内,销售商每次进货量相同,生产商按照EOQ模型采购原材料。以最小化供应链系统的总运营成本为目标,构建一个混合整数非线性规划模型,寻找销售商最优订货方案和生产商最佳生产策略。首先利用网络优化方法求解生产商的最优生产计划,其次利用定界穷举法寻求销售商最优的订货周期,给出了具体的计算方法和Matlab程序。通过算例分析验证了算法的有效性,并研究了各参数对最小费用及最优解的影响。     

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。     

关于信用期内含缺陷产品EOQ模型

考虑到在实际中供应链上游供应商提供给下游零售商的信用支付期通常为一个订货周期,建立了缺陷率服从一定分布的缺陷产品在信用支付策略下的最优订货批量模型.模型中允许缺货发生并且以最大期望利润为目标函数,通过分析得到模型最优解.最后给出仿真实验,并且分析了模型参数变化对最优解的影响.     

供应链买卖双方协调订货模型

供需关系贯穿供应链的整个过程;然而,如何促使非一体化供应链协调问题在实践中是非常重要的.因此,供需双方订货批量的研究是供应链管理的一个重要内容之一.本文以订单方式为背景,针对供应链环境下单个供应商和多个订货商在非合作情况下的订货模型进行讨论,并在此基础上给出了一个改进后的线性价格折扣策略,该策略同时考虑了增量折扣和减量折扣两种情况,同时给出了供需上双方订货的S tackelberg博弈模型.数字实验结果表明该折扣模型对于改善供应链运作协调是相当有效的.     

基于学习效应的供应链信息共享研究

供应链中存在着广泛的信息共享,既包括上下游企业间的纵向性共享,也包括同层企业间的横向信息共享.以一个具有学习效应的供应链为研究对象,为研究信息共享对分散型供应链中零售商决策的影响,提出了一个具有横向信息共享的供应链模型.以Cournot博弈为研究手段,求解了零售商的均衡订货决策和信息共享策略.在此模型中,生产商为多个零售商提供类似的产品,每个零售商具有自己独立的终端市场.零售商面对单周期需求,该需求可以在本周期内满足或者在第二阶段延迟交货.由于学习效应的存在,第二阶段生产商的批发价格是第一阶段总订货量的减函数.零售商在观察到自身的需求之前,达成信息共享的协议.研究结果表明,当第一阶段的均衡订货数量低于需求时,零售商间无共享私有信息的动机,该结果和寡头模型信息共享的相关结果相反.除此之外,在一个总体需求稳定的市场中,信息共享的影响随着零售商数量的增加而递减.此结果对企业在不同市场情况下选择信息共享策略具有重要价值.     

易逝品价格连续下降情况下带有随机需求的供应链协调

本文研究了短生命周期产品价格随时间连续下降情况下单供应商和单销售商渠道中的供应链协调。分别建立了分散决策、集中决策和基于收入共享合同的最优订货策略模型,讨论了模型的相关性质,提出了一种基于收入共享合同的供应链协调策略,来实现整个供应链的协调。并指出该策略不仅适用于价格时变情况,能实现整个供应链的期望利润最大化,并且具有很好的适用性。最后,用实例仿真验证了本文所给出的模型和策略的有效性。     

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.     

资金约束供应链中最优融资和生产决策研究

研究了由单个生产商和单个零售商所构成的两级供应链的融资和生产决策问题.分别以生产商和商业银行作为供应链上的领导者,研究两者所做出的最优融资/生产决策与放贷策略.研究结果表明:生产商的最优产量相对于经典报童模型下的产量是下偏的,且与银行的贷款利率呈现出负相关的关系;银行获得最优收益时,生产商的产量相对于其最优产量是上偏的,且银行的最优放贷额和贷款利率被显示给出.     

考虑需求依赖库存及分摊运费的供应链协调

针对单个销售商和单个生产商组成的两层供应链,假定需求依赖于当前库存水平,考虑运输费用与订货量相关,研究了采用分摊运费策略的供应链协调问题.首先在分散式系统下,建立了供需双方的Stackelberg博弈模型;然后设计了分担运输费用的协调策略,建立了供需双方的利润模型.研究结果表明该协调策略不仅能提高供需双方的利润,而且使得供应链达到了完美协调.     

条件延期付款下一体化可控提前期模型研究

在一体化决策的供应链中,假设提前期与提前期成本服从幂函数关系,生产商允许零售商延期付款,但需要在订货时预付部分货款。首先,在延迟付款期给定时,通过建立该问题的数学模型,证明了不考虑决策变量整数约束时,系统存在唯一最优生产量、提前期和生产商每个生产周期内的运输批次,使得供应链总成本最小,并设计求解算法对问题进行了求解。以此为基础,假设延迟付款期是零售商订货量的增函数,结合模型的解析性质,给出了新的求解算法。最后通过数值算例和敏感性分析,说明了所得结论及其管理启示。     

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。     

Coordination mechanism for a deteriorating item in a two-level supply chain system

The subject of the coordination between the suppliers and the buyers in multi-echelon inventory-distribution systems has been studied by many researchers. This paper considers a supply chain including a manufacturer and several buyers and assumes that the inventory items deteriorate over time and its inventory level decreases. In order to determine the order policies, coordination over the supply chain is achieved by scheduling the buyers’ delivery days and their coordination with the manufacturer’s production cycle. A mathematical model is developed and analyzed. To test the efficiency of the proposed model, two other models with the supposition of lot-sizing policies with common order cycle and independent deciding are also developed. In comparison to the other two models, the numerical results show that the synchronizing model of production and delivery cycles works better and has less total cost. In addition, in order to encourage the buyers in cooperation, a model on profit sharing is proposed that equitably shares the total savings with all the parties.     

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。     

Modeling and mitigating supply chain disruptions as a bilevel network flow problem

Years of globalization, outsourcing and cost cutting have increased supply chain vulnerability calling for more effective risk mitigation strategies. In our research, we analyze supply chain disruptions in a production setting. Using a bilevel optimization framework, we minimize the total production cost for a manufacturer interested in finding optimal disruption mitigation strategies. The problem constitutes a convex network flow program under a chance constraint bounding the manufacturer’s regrets in disrupted scenarios. Thus, in contrast to standard bilevel optimization schemes with two decision-makers, a leader and a follower, our model searches for the optimal production plan of a manufacturer in view of a reduction in the sequence of his own scenario-specific regrets. Defined as the difference in costs of a reactive plan, which considers the disruption as unknown until it occurs, and a benchmark anticipative plan, which predicts the disruption in the beginning of the planning horizon, the regrets allow measurement of the impact of scenario-specific production strategies on the manufacturer’s total cost. For an efficient solution of the problem, we employ generalized Benders decomposition and develop customized feasibility cuts. In the managerial section, we discuss the implications for the risk-adjusted production and observe that the regrets of long disruptions are reduced in our mitigation strategy at the cost of shorter disruptions, whose regrets typically stay far below the risk threshold. This allows a decrease of the production cost under rare but high-impact disruption scenarios.

     

Economic selection of process mean for single-vendor single-buyer supply chain

Process mean selection for a container-filling process is an important decision in a single-vendor single-buyer supply chain. Since the process mean determines the vendor’s conforming and yield rates, it influences the vendor–buyer decisions regarding the production lot size and number of shipments delivered from the vendor to buyer. It follows, therefore, that these decisions should be determined simultaneously in order to control the supply chain total cost. In this paper, we develop a model that integrates the single-vendor single-buyer problem with the process mean selection problem. This integrated model allows the vendor to deliver the produced lot to buyer in number of unequal-sized shipments. Moreover, every outgoing item is inspected, and each item failing to meet a lower specification limit is reprocessed. Further, in order to study the benefits of using this integrated model, two baseline cases are developed. The first of which considers a hierarchical model where the vendor determines the process mean and schedules of production and shipment separately. This hierarchical model is used to show the impact of integrating the process mean selection with production/inventory decisions. The other baseline case is studied in the sensitivity analysis where the optimal solution for a given process is compared to the optimal solution when the variation in the process output is negligible. The integrated model is expected to lead to reduction in reprocessing cost, minimal loss to customer due to the deviation from the optimum target value, and consequently, providing better products at reduced cost for customers. Also, a solution procedure is devised to find the optimal solution for the proposed model and sensitivity analysis is conducted to investigate the effect of the model key parameters on the optimal solution.     

Synchronization in supply chains: implications for design and management

Supply chain management literature calls for coordination between the different members of the chain. Materials should be moved from one supplier to the next according to a just-in-time schedule. In this paper, we show that for many supply chain configurations, complete synchronization will result in some members of the chain being ‘losers’ in terms of cost. We develop an algorithm for optimal synchronization of supply chains and provide some guidelines for incentive alignment along the supply chain. In developing the model, we use the economic delivery and scheduling problem model and analyze supply chains dealing with single and multiple components. For single-component supply chains, we derive a closed-form expression for the optimal synchronized cycle time. For multi-component supply chains, we develop an algorithm for finding the optimal synchronized cycle time. We test the performance of the algorithm and show that it provides optimal solutions for a wide range of problems. We illustrate the models with numerical examples.     

政府奖惩下供应链合作减排与低碳宣传的动态优化

为减少生产过程中碳排放对环境带来的不利影响,考虑到政府对制造商采取奖惩措施,以此为背景,针对供应链长期合作减排、低碳宣传的问题,构建微分博弈模型。考虑到产品需求受碳排放量和零售商低碳宣传努力的共同影响下,得出并分析了分散式和集中式决策下制造商和零售商的反馈均衡策略及产品碳排放量的最优轨迹,发现产品碳排放量的最优轨迹具有多种敛散性,且在集中式决策下实现了供应链利润和环境绩效的双赢。此外,还分析了政府奖惩力度对产品碳排放量的影响。最后结合算例对模型进行分析,为供应链的低碳化管理和政府奖惩政策的制定提供了理论参考。     

供应链互补产品广告投入和捆绑销售联合决策研究

以一个制造商和一个零售商的供应链为研究对象,制造商生产两种互补产品,零售商可选择分开或捆绑两种销售策略。考虑互补品的负交叉弹性和广告外部性的特点,构建基于溢出效应的需求模型,运用博弈论的方法,求解零售商采取分开和捆绑两种销售策略时的均衡结果。通过比较不同销售策略下的均衡结果及利润关系,探讨在分散式和集中式两种情况下,零售商的最优广告投入和捆绑销售的联合决策问题。最后,通过数值算例,讨论产品互补程度和广告成本系数对决策结果的影响。研究结果表明,无论是在分散式还是集中式决策下,当产品互补程度较高或广告成本系数低时,分开销售是占优策略而广告费用较高;当产品互补程度较低且广告成本系数高时,捆绑销售是占优策略且广告费用较低。     

A bargaining model with asymmetric information for a single supplier–single buyer problem

Banerjee’s joint economic lot size (JELS) model represents one approach to minimizing the joint total relevant cost of a buyer and a supplier by using a joint optimal order and production policy. The implementation of a jointly optimal policy requires coordination and cooperation. Should the buyer have the market power to implement his own optimal policy as that one to be used in the exchange process no incentive exists for him to choose a joint optimal policy. A joint policy can therefore only be the result of a bargaining process between the parties involved. The supplier may make some sort of concession such as a price discount or a side payment in order to influence the buyer’s order policy. A critical assumption made throughout in supply chain literature is that the supplier has complete knowledge about the buyer’s cost structure. Clearly, this assumption will seldom be fulfilled in practice. The research presented in this paper provides a bargaining model with asymmetric information about the buyer’s cost structure assuming that the buyer has the power to impose its individual optimal policy.     

Analysis of a fuzzy economic order quantity model for deteriorating items under retailer partial trade credit financing in a supply chain

This paper investigates the economic order quantity (EOQ) — based inventory model for a retailer under two levels of trade credit to reflect the supply chain management situation in the fuzzy sense. It is assumed that the retailer maintains a powerful position and can obtain the full trade credit offered by the supplier yet the retailer just offers a partial trade credit to customers. The demand rate, holding cost, ordering cost, purchasing cost and selling price are taken as fuzzy numbers. Under these conditions, the retailer can obtain the most benefits. Study also investigates the retailer’s inventory policy for deteriorating items in a supply chain management situation as a cost minimization problem in the fuzzy sense. The annual total variable cost for the retailer in fuzzy sense is defuzzified using Graded Mean Integration Representation method. Then the present study shows that the defuzzified annual total variable cost for the retailer is convex, that is, a unique solution exists. Mathematical theorems and algorithms are developed to efficiently determine the optimal inventory policy for the retailer. Numerical examples are given to illustrate the theorems and the algorithms. Finally, the results in this paper generalize some already published results in the crisp sense.