Interdependent Network Recovery Games

Recovery of interdependent infrastructure networks in the presence of catastrophic failure is crucial to the economy and welfare of society. Recently, centralized methods have been developed to address optimal resource allocation in postdisaster recovery scenarios of interdependent infrastructure systems that minimize total cost. In real-world systems, however, multiple independent, possibly noncooperative, utility network controllers are responsible for making recovery decisions, resulting in suboptimal decentralized processes. With the goal of minimizing recovery cost, a best-case decentralized model allows controllers to develop a full recovery plan and negotiate until all parties are satisfied (an equilibrium is reached). Such a model is computationally intensive for planning and negotiating, and time is a crucial resource in postdisaster recovery scenarios. Furthermore, in this work, we prove this best-case decentralized negotiation process could continue indefinitely under certain conditions. Accounting for network controllers' urgency in repairing their system, we propose an ad hoc sequential game-theoretic model of interdependent infrastructure network recovery represented as a discrete time noncooperative game between network controllers that is guaranteed to converge to an equilibrium. We further reduce the computation time needed to find a solution by applying a best-response heuristic and prove bounds on ε-Nash equilibrium, where ε depends on problem inputs. We compare best-case and ad hoc models on an empirical interdependent infrastructure network in the presence of simulated earthquakes to demonstrate the extent of the tradeoff between optimality and computational efficiency. Our method provides a foundation for modeling sociotechnical systems in a way that mirrors restoration processes in practice.     

Stochastic Optimal Control for Staffing and Backlog Policies in a Two‐Stage Customized Service Supply Chain

Motivated by an oilfield services industry case study, we investigate the dynamic behavior of customized service supply chains by developing a two‐stage serial staffing model. Each stage holds no finished goods inventory, but rather only backlogs that can be managed by adjusting staffing levels. We develop optimal control policies to balance backlog costs against hiring and firing personnel costs'assuming shared backlog information—under both centralized and decentralized control. We examine when there is sufficient economic incentive for two completely decentralized stages to begin: (1) to share backlog information without centralizing control, or (2) to completely centralize control. These switching points are determined by the relative service and personnel costs of the two stages. From these results, we show that decentralizing control in many cases does not materially worsen performance, so long as information is shared. Moreover, in some cases, even sharing information is of only marginal benefit.     

基于碳标签制度的两级供应链协调机制研究

以市场需求随机的视角建立Stackelberg博弈模型,研究基于碳标签制度的供应商和零售商组成的两级供应链协调策略。模型引入产品碳足迹e₁作为决策变量,分别研究了在收益共享与成本共担契约下集中决策和分散决策中决策变量最优解及最优利润的变化情况。研究结果表明,在考虑碳排因素时集中决策相比于分散决策具有明显的优势;在参数满足一定条件下零售商通过与供应商共担碳减排成本,可以实现利润的增长,初步验证模型的契约设计的有效性。     

考虑消费者低碳偏好的供应链减排微分博弈模型研究

针对由一个供应商和一个制造商构成的两级供应链,考虑消费者的低碳偏好和碳交易政策,建立分散决策和集中决策两种情形下的微分博弈模型解决供应链动态优化问题,比较两种情形下的最优均衡反馈策略、减排量的最优轨迹及最优利润,提出减排策略。通过数值仿真,进一步验证了命题的有效性;通过对消费者低碳偏好及碳交易价格进行灵敏度分析发现：随着低碳偏好的增加,供应商和制造商的减排量和供应链系统的利润均增加,并且政府在规划期内应及时调整碳交易政策,达到激励企业减排的效果。     

差别定价闭环供应链协调应对生产成本扰动研究

文章以一个新产品和再造品存在差别定价的闭环供应链为研究对象,考虑突发事件干扰新产品和再造品生产成本的情况,研究了集中式决策闭环供应链的应对策略,以及收益共享契约协调分散式决策闭环供应链的问题。研究表明:在突发事件干扰下,对于集中式决策闭环供应链,当两种产品生产成本的扰动程度均较小时,原稳定环境下的最优产量决策具有一定的鲁棒性;至少一种产品生产成本的扰动程度较大时,受干扰程度较大的产品应按其生产成本扰动相反的方向进行调整其原稳定环境下的最优产量决策,而另一种产品最优产量的调整方向受扰动程度较大产品生产成本的扰动程度、两种产品的替代系数以及额外单位生产或处理成本的影响。对于分散式决策闭环供应链,两种产品生产成本的扰动程度均较小时,原稳定环境下的收益共享契约仍有效;至少一种产品生产成本的扰动程度较大时,则需改进原稳定环境下的收益共享契约以再次协调闭环供应链,且改进后的契约也能够协调稳定环境下的闭环供应链。最后,通过数值算例验证了模型的合理性及契约协调的有效性。     

基于开工柔韧性的关键链项目缓冲分配方法

缓冲应该进行集中式还是分散式管理是项目缓冲管理的一个核心问题，经典缓冲管理方法没有对此进行研究。基于此，本文在考虑开工柔韧性的情况下，研究并比较分析了两种项目缓冲的分配模式。通过对两种缓冲管理模型的研究，结合MATLAB仿真结果发现，缓冲集中式管理模式在考虑开工柔韧性的情况下，主要通过活动资源提前就位来抓住项目活动可能出现的提前完工机会，即通过可能的成本增加来换取可能的工期降低。仿真结果显示，在这种模式下，项目工期提前了8.67%，而总成本只上升了2.02%（主要是因为增加了资源库存成本和计划变动成本），由此可见，集中式缓冲管理模式可以有效降低工期。而缓冲分散式管理模式则是现有缓冲管理方法的延伸，在考虑开工柔韧性的情况下，将项目计划做出不同程度延缓，相较于缓冲集中式管理没有了库存成本的增加，实验结果表明，当活动完工率落在概率分布函数的50%~60%之间时可得到项目的最佳缓冲分散程度。     

Budgets for integrating decentralized investment and production planning

Planning for an economic enterprise can be dichotomized into short-run production planning and longer-run investment planning. Usually these problems are treated as if they were separate, if not independent. This paper briefly reviews the separate approaches to optimal production decision making and investment planning, ‘fusing’ these models in order to consider the two issues simultaneously. The resulting ‘fused’ model is used to illustrate several difficulties which result from an intuitive synthesis of the independent solutions of the production problem and the investment problem. An integrated model is presented representing a centralized simultaneous solution for decision variables from the two functional fields. The paper compares and contrasts the synthesis of separate functional models to the decomposition of a simultaneous model of those functional areas. A result of this comparison is a theoretical justification for operating budgets and revenue targets as organizational mechanisms for achieving coordinated plans among decentralized planning units. Further, the set of conditions are identified under which the two approaches to simultaneous decision making are equivalent.     

A Note on Determining Optimal Selling Price and Lot Size Under All-Unit Quantity Discounts

A recent study conducted by Abad [1] described a method of determining the optimal price and lot size when the supplier offers all-unit quantity discounts. The author developed a procedure using centralized and decentralized approaches. According to the author's suggestion, further study is necessary to determine if the decentralized approach always provides an optimal solution. In the present study, an attempt is made to investigate the uniformity between the centralized and decentralized approaches and to verify whether the decentralized approach always yields optimal solutions.     

考虑延时效应的供应链动态合作广告策略研究

广告的延时效应是供应链广告过程中的普遍现象,对供应链合作广告策略的制定具有重要影响.文章研究当产品品牌信誉受广告延时效应影响时供应链的合作广告策略问题,建立了含有时间延迟的品牌信誉动态模型和考虑品牌信誉的产品销售量模型.运用极大值原理,得到了制造商和零售商在分散式决策和集中式决策下的最优广告投入、品牌信誉和利润,以及分散式决策下制造商的最优合作广告参与率.研究发现:在集中式决策下制造商和零售商的最优广告投入和产品销售量均高于分散式决策下的相应值;延迟时间存在一个阈值,当延迟时间低于该阈值时,集中式决策下的供应链利润较高,反之则分散式决策下的供应链利润较高.研究结果为供应链合作广告策略的制定及供应链决策机制的选择提供了一定的参考.最后,通过数值算例分析了广告延迟时间对供应链最优广告策略及决策机制的影响.     

Aggregate planning in decentralized organizations

This paper deals with aggregate planning problems in decentralized organizations, i.e. organizations where the suborganizations have a fair amount of autonomy in control because information load, uncertainty and fast changing circumstances limit the possibilities of centralized control. The functions of aggregate planning, its place in the overall control structure of the company and the control variables involved are discussed and subsequently the additional complications of a decentralized setting. As a typical example of aggregate planning problems in a network of semi-autonomous organizations the so-called ‘internal business cycle’ is discussed: due to this phenomenon the network is not able to follow smoothly its final demand but moves from shortages in one period to surplusses in another. The causes, various positive feedback mechanisms through variations in the buffers between the units, are analyzed and illustrated with a simple simulation model. The paper concludes with a discussion on the use of aggregate planning to improve the control of the network and to dampen this internal business cycle.     

需求和零售商购买成本同时扰动的供应链应急协调

供应链的契约协调机制是供应链管理的重要内容,突发事件下的供应链协调机制是近年来的研究热点。 研究了在单制造商单零售商组成的供应链中,假设生产成本是其生产数量的凸函数下,当市场需求为零售价格的非线性函数,突发事件造成需求和零售商购买成本同时发生扰动时,集权、分权供应链应对突发事件的最优策略。 首先证明了稳定环境下的数量折扣契约可以实现该供应链的协调,在集权式决策下,供应链的原有生产计划对突发事件具有一定的鲁棒性,但是当突发事件造成的扰动超过一定幅度时,供应链的协调将会被打破,供应链系统必须改变生产计划才能实现其利润最大化。 在分权式决策下,供应链的原数量折扣契约不能使扰动后的供应链达到协调,因此,设计了新的数量折扣契约来使扰动后的供应链达到协调。最后给出一个算例验证了相关结论。     

具有风险规避销售商的供应链最优回购契约

在销售商风险规避下,运用CVaR方法研究了供应商在直营渠道（集中式供应链）和非直营渠道（分散式供应链）下回购契约的设计问题。刻画了集中式供应链下回购契约完成渠道协调的充要条件,求解了分散式供应链的最优回购契约。比较分析了集中式和分散式供应链下回购契约的差异,得到以下结论：相对于集中式供应链,供应商在分散式供应链中趋向于设定更高的批发价格,或更低的回购价格。讨论了销售商的风险规避度对契约设计和供应商收益的影响,研究表明：销售商越规避风险,供应商的收益越低。最后提供一个案例讨论了模型在现实中的应用。     

供应商保鲜努力的生鲜农产品双渠道供应链协调决策研究

在互联网迅猛发展的时代,生鲜农产品双渠道营销模式是供应商的最佳选择,如何发挥双渠道优势,实现渠道共赢是目前研究的热点。以供应商主导的双渠道供应链为研究对象,考虑新鲜度衰减且扰动需求和供应商保鲜努力,对比分析集中和分散决策模型,论证构建协调模型的必要性。从渠道合作和利润最大化的角度出发,设计两部定价契约、批发价协调契约和由成本分担与补偿策略构成的混合协调契约,三种契约均能在一定范围内有效实现供应链协调,提高各成员的利润。最后,对比分析所设计协调契约以认识其本质,并通过数值分析验证其有效性。     

考虑在线评论的双渠道供应链定价与服务决策

在集中与分散决策情形下,分别构建不考虑和考虑在线评论的双渠道供应链博弈模型,探讨在线评论背景下供应链的定价和服务投入决策,并分析在线评论对供应链最优决策和利润的影响。研究表明:在线评论会激励零售商提高服务投入水平;当评论有效性水平足够高时,其对制造商有利,当评论正向作用较强且精度足够高时,其对零售商有利;与集中决策相比,分散决策下评论精度提高对供应链系统更加不利;此外,当评论有效性水平足够高时,零售商服务投入可有效消除供应链双重边际效应。     

双边网络环境下考虑消费者行为的两期供应链回收定价模型研究

闭环供应链管理是促进经济与环境双重效益提高的有效途径，已成为电子废弃物回收利用的核心解决方案。本文考虑包括制造商和第三方回收平台组成的闭环供应链模型，构建了完全垄断的两期动态博弈双边平台，分析和比较了分散决策和集中决策下闭环供应链的最优回收定价和利润，并利用收益共享契约来实现闭环供应链帕累托改进，最后用数值仿真分析了再制造比例、用户对平台利润贡献率对供应链利润的影响，验证了契约协调的有效性。研究表明：交叉网络外部性强度与平台向两边征收的价格、各主体利润和总体利润存在相关关系。第三方回收平台通过补贴消费者可有效增加回收效用，提高了回收率与消费者回收意识。实施收益共享契约的互利性使各主体积极主动实施契约，提高了各方与总体利润。     

供需同时不确定关系型供应链契约设计与决策

在同时面临随机产出（random yield）和随机需求的供应链中,引入基于现实应用设计的具有声誉效用机制和信任机制的承诺契约,同时考虑紧急采购,建立多重不确定关系型供应链决策模型。分析该类型集中式供应链（CSC：centralized supply chain）和以Stackelberg博弈为基础的分散式供应链（DSC：decentralized supply chain）的最优供应、采购策略存在性及其条件,应用逆向推导法探讨供需双方的博弈过程;通过绝对和相对指标分析供应链及其成员的绩效;结合理论推导和数值试验对承诺契约参数、供应链及其成员最优策略和期望收益做关于供需不确定性、紧急采购价格的敏感性分析。     

考虑参考减排努力水平效应的联合减排与竞争动态策略研究

考虑到参考减排努力水平效应，构建了一个包括两个竞争的中小低碳代工制造商和一个品牌商的供应链，借助微分博弈理论研究了联合减排和广告的动态策略以及供应链协调问题。先后分析了供应链在分散决策和合作决策中的均衡策略，比较了两种决策模式下减排努力水平、广告水平以及供应链总利润现值的差别，发现制造商边际收益较低时，在合作决策中减排努力水平更高，否则在分散决策中减排水平更高；品牌商在合作与分散决策中广告水平的高低不取决于品牌商的边际收益而取决于制造商边际收益的相对高低，合作价值是品牌商边际收益的减函数，借助数值模拟分析了记忆效应和参考效应参数对供应链总利润现值的影响。通过设计低碳代工制造商和品牌商之间相互分担对方的减排成本和广告成本的契约，实现了供应链协调，达到了在合作决策时的总利润，并比较了竞争的减排代工制造商和品牌商在分散决策和双向成本分担契约中的利润现值差异，数值分析发现简单的双向成本契约并不能实现帕累托改进，本文提供了转移支付的思路以实现契约自执行性。     

基于不同权力结构的废旧产品回收再制造决策分析

本文研究了制造商主导、回收商主导、垂直纳什均衡以及集中式决策四种不同权力结构下的废旧产品回收再制造问题,给出并比较了四种结构下决策变量的最优解。研究表明:与集中式决策相比,三种分散式情形下的系统效益非最优;垂直纳什均衡时的系统效益严格优于制造商主导时;当回收商主导逆向供应链时,在某些条件下能够达到集中式决策的水平;相反,制造商主导和垂直纳什均衡时则无法达到。对制造商主导和回收商主导两种情形,利用费用共享契约和二部定价契约进行了协调。     

基于消费者需求差异和渠道权力结构差异的MT-CLSC定价、效率与协调研究

相比其他回收模式,制造商负责回收废旧品的闭环供应链（简称MT-CLSC）在节约成本、提高系统利润方面更加有效。针对MT-CLSC渠道权力结构的差异,结合消费者对新产品和再造品的偏好及其影响,文章构建了四种不同的MT-CLSC模型,分别是制造商和零售商合作决策的集中式模型、制造商权力大于零售商权力的分散式决策模型、制造商权力小于零售商权力的分散式决策模型、制造商和零售商权力均等的分散式决策模型,根据各个模型的不同特点,计算出各模型的最优定价策略、回收策略以及相应的利润、渠道效率。然后,借助数值分析的方法,对不同模型的定价策略、回收策略、利润、渠道效率进行比较。研究发现：（1）各模式中,渠道利润以及MT-CLSC各成员的利润均随着消费者偏好系数的增大而减少;（2）在分散决策下,制造商和零售商的利润均与双方的权力相关,权力越大,相应的利润越多;（3）分散决策模式中,制造商和零售商权力均等的模式渠道效率最高,效率最低的是零售商占主导地位的权力结构;（4）制造商和零售商合作的集中式决策模式是最优的决策模式,此时新产品、再造品的定价最低,废旧品的“回收--需求率”最低,而渠道利润却最高,但是这种模式通过协调机制才能实现。为此,文章最后设计了有效的协调机制,使得集中式模式得以实现。本文的研究结论对丰富完善闭环供应链理论和推广应用闭环供应链具有一定的指导作用。     

Impact of Retailers with Knowledge of Supplier's Inventory on Supply Chain Performance

We model a supply chain consisting of a supplier and multiple retailers facing deterministic demand. We denote some retailers as strategic in the sense that given the supplier inventory information, they will implement the optimal stocking policy by incorporating such information. On the other hand, some retailers are denoted as naïve in the sense that they ignore supply information and resort to a simplistic ordering policy. Naïve retailers learn the optimal policy over time and adjust their orders accordingly. We study the dynamics of this game and investigate the impact of such strategic and naïve retailers on the cost, ordering pattern and stocking policies of all parties. We analyze the supply chain under two scenarios: the centralized supply chain where the objective is to minimize the total supply chain cost, and the decentralized supply chain where each self‐interested player minimizes its own cost in a Stackelberg game setting. We fully characterize the optimal policies under both centralized and decentralized scenarios and show that, surprisingly, the supply chain might be better off by virtue of naïve retailers. The result is driven by the fact that strategic and naïve players’ decisions shift the positioning of inventory in the supply chain with its final impact being determined by the relative costs of different retailer‐types. Our results also offer managerial insights into how access to supply information can improve supply chain performance.