一种三重接触架构下的退货物流优化方法研究

分析了闭环控制系统架构所涉及到的供应链逆向物流中,针对不确定的退货物流回收再制造的各个环节的特点,利用UML建模语言,从单一营销回收渠道和电子商务环境下的双源营销回收渠道两个方面对影响闭环回收再制造的众多因素进行了分析,建立了产品再制造过程的类图和状态图,给出了基于Arena仿真工具的一般回收再制造架构和双源渠道回收再制造架构,在此基础上利用三重生产架构实现了系统集成、科技创新和第三方外包的产品增值再制造,达到了对原来两种架构方案的优化。应用表明,该方案优化了整个闭环再制造供应链系统的运作。     

基于复杂网络的供应链网络鲁棒性分析

供应链网络经常面临各种突发事件的干扰,使网络用户受到损失。为更好地提高供应链网络的鲁棒性能,采用复杂网络理论构建了带有可调参数的供应链网络演化模型。在给出供应链网络鲁棒性新测度的基础上,分析了在受到随机干扰和选择性干扰的情形下,用不同拓扑结构的供应链网络模型进行仿真分析。仿真结果表明:供应链网络的拓扑结构对供应链网络的鲁棒性有重要的影响,通过调整模型中的参数,改变网络的演化机制,可以达到改善供应链网络鲁棒性的目的,并对于提高供应链网络的抗干扰能力具有重要的现实和理论意义。     

B2B电子市场下供应链期权合同协调模型与优化

研究B2B电子市场下双源渠道的供应链期权合同协调模型与优化问题.在需求不确定条件下,推导了传统供应链中分销商的最优批量定货量和最优期权购买量,以及供应商的最优生产量.建立了B2B电子市场下的供应链期权合同模型,结合长期合约的稳定性和现货采购的灵活性,讨论了分销商和供应商的最优决策.最后从渠道协调的角度,讨论了传统供应链和B2B电子市场下的期权合同能有效协调供应链的充分条件.     

不正常航班恢复的飞机和乘客优化调配模型

现实生活中有很多因素影响航空公司的正常运营,比如飞机故障、极端天气、航空管制等,这些问题的产生不仅增加了航空公司的运营成本,而且还给乘客带来许多损失。为了降低航空公司的运营成本和乘客的损失,从飞机调配和受干扰乘客的重新调配出发构建模型,通过IBM ILOG CPLEX软件对两个模型进行求解,并获得了备用恢复行程的飞机调配方案和受干扰乘客的重新调配方案。通过实际算例验证了该模型的有效性和实用性。     

分布式决策闭环供应链协调运作研究进展

在分析闭环供应链中存在的分布式决策问题及其产生原因的基础上,说明了分布式决策闭环供应链协调运作策略设计的重要性和研究意义,对闭环供应链的协调、运作以及运作过程中的不确定性和鲁棒性等问题的研究现状进行了综述,探讨了分布式决策闭环供应链协调运作研究的若干前瞻性问题.     

制造商主导型双渠道供应链协调决策模型

以制造商主导型供应链为研究对象, 分析双渠道供应链协调策略问题. 引入双渠道价格敏感系数和竞争系数两个变量, 分别建立双渠道供应链集中决策、分散决策和协调决策的3 种模型. 研究结果表明, 不同合同策略协调后, 零售商和供应链整体收益增加; 经两部定价和批发价格合同协调, 零售商需要支付固定费用给制造商才能够达到协调, 而经Shapley 值法分配合同协调, 则双渠道供应链可直接达到协调效果.

     

需求和回收努力扰动下闭环供应链定价与协调

针对干扰事件下由单个制造商和单个零售商组成的闭环供应链系统, 建立制造商为主导的Stackelberg博弈模型, 首先分析了数量折扣契约对闭环供应链的协调作用, 然后分析了数量折扣契约应对干扰事件的协调作用。结果表明, 当干扰事件引起市场规模、再制造成本、回收努力同时扰动时, 原契约具有一定鲁棒性; 当扰动超出一定范围时, 原有的协调被打破; 为此, 给出改进的数量折扣契约具有抗干扰事件性, 并讨论闭环供应链成员的最优利润分配策略, 最后通过数值实验来验证结论的有效性。     

不同竞争环境下损失厌恶与网络销售效率对双渠道供应链的影响

考虑由电商平台和制造商组成的双渠道供应链,制造商存在网络销售效率问题,消费者存在损失厌恶心理,在不同竞争环境下,分析网络销售效率、损失厌恶对企业定价和收益的影响.结果表明,在Nash均衡博弈、制造商主导Stackelberg博弈和电商平台主导Stackelberg博弈下,网络销售效率的下降导致网络销售价格和电商平台收益上升,制造商收益和供应链收益下降,网络销售价格在电商平台主导Stackelberg博弈下最大,在制造商主导Stackelberg博弈下最小;损失厌恶的增大导致网络销售价格、企业和供应链收益均下滑,企业收益在自身企业主导Stackelberg博弈下最大,在对方企业主导Stackelberg博弈下最小;供应链收益在供应链集中下最大,在电商平台主导Stackelberg博弈下最小.     

非匹配离散系统无抖振鲁棒准滑模控制

研究离散准滑动模态的鲁棒性恢复和抖振削弱问题。针对一类同时含有匹配建模误差和非匹配外界干扰不确定离散系统,设计一种基于解耦干扰补偿器的鲁棒准滑模控制方案。为保证系统的鲁棒性,针对非匹配外界干扰设计一种改进的解耦干扰补偿器,估计误差有界收敛。通过引入幂次函数设计鲁棒离散准滑模控制器,消除系统抖振,给出切换函数准滑模带,并证明了闭环系统离散准滑动模态的稳定可达性。最后通过仿真验证了所提出控制方案的有效性。     

考虑建议零售价的双渠道供应链批发价格模式选择

对由制造商网络直销渠道和零售商传统渠道构成的双渠道供应链系统进行研究。首次在建议零售价背景下研究了批发价格模式选择问题,运用制造商主导的Stackelberg博弈,得出了供应链各成员的价格均衡策略。综合考虑零售商谈判能力和和消费者对渠道的偏好度,对比分析了不同批发价谈判模式下的制造商利润、零售商利润和供应链利润。结果表明,制造商可通过建议零售价调整市场价格;从供应链总体或者零售商角度,以直销价格为基准确定批发价格是最优的;制造商倾向于单独确定批发价格,但当零售商谈判能力较弱,且网络渠道基本市场份额偏大时,也可接受以网络直销价为基准确定批发价格。     

A supply chain disruption recovery strategy considering product change under COVID-19

A recent global outbreak of Corona Virus Disease 2019 (COVID-19) has led to massive supply chain disruption, resulting in difficulties for manufacturers on recovering their supply chains in a short term. This paper presents a supply chain disruption recovery strategy with the motivation of changing the original product type to cope with that. In order to maximize the total profit from product changes, a mixed integer linear programming (MILP) model is developed with combining emergency procurement on the supply side and product changes by the manufacturer as well as backorder price compensation on the demand side. The model uses a heuristic algorithm based on ILOG CPLEX toolbox. Experimental results show that the proposed disruption recovery strategy can effectively reduce the profit loss of manufacturer due to late delivery and order cancellation. It is observed that the impact of supply chain disruptions is reduced. The proposed model can offer a potentially useful tool to help the manufacturers decide on the optimal recovery strategy whenever the supply chain system experiences a sudden massive disruption.     

GBOM-oriented management of production disruption risk and optimization of supply chain construction

A generic bill-of-materials (GBOM) describes demand for materials and their proportional relations to a family of products. Supply chain constructed from the perspective of the GBOM is able to respond swiftly to market demand and lean production can be achieved by managing the total cost of supply chain effectively. Based on the GBOM, this paper examines the control of production disruption risk related to supply chain and investigates the uncertainty of production in supply chain enterprises for the purpose of achieving optimal profits in supply chain. As the production disruption risk is controlled at a certain level, the selection model of supply chain partners, which is specific and more feasible, can be constructed. A combination of random simulation and neural network is deployed to approximate uncertain function, and genetic algorithm and simulated annealing arithmetic are also used to approximately achieve the optimal scheme of supply chain construction in the context of uncertainty.     

联合促销和风险规避下应对突发事件的供应链协调策略

针对联合促销和风险规避下考虑突发事件的供应链协调问题,应用条件风险值度量制造商和零售商的风险价值,引入回购契约协调供应链,分别构建应对常规和非常规突发事件的供应链协调模型.研究表明,常规突发事件下,订货量、促销和契约参数具有一定的稳定性,当需求扰动较大时,供应链协调被打破,而非常规突发事件下,需求扰动打破供应链协调,通过调整契约参数能够使供应链重新达到协调状态.     

A study of emergency management of supply chain under supply disruption

Emergency is an important factor resulting in supply disruption risk. How to deal with emergency in supply chain arouses managers’ and researchers’ attention in recent years. In order to improve the effect of supply disruption risk management under this situation, this paper builds the supply disruption Emergency Management Model of supply chain from the angle of risk management and discusses whether the decision-making mechanism of the case-based reasoning can bring the better effect for supply disruption by using computational experiment. The results mainly show that the mechanism of risk assessment, risk identification, risk control and risk evaluation based on the case-based reasoning can effectively deal with supply disruption risk, and bring more profit and better service level for the members of supply chain.     

Modelling inter-supply chain competition with resource limitation and demand disruption

This paper proposes a comprehensive model for studying supply chain versus supply chain competition with resource limitation and demand disruption. We assume that there are supply chains with heterogeneous supply network structures that compete at multiple demand markets. Each supply chain is comprised of internal and external firms. The internal firms are coordinated in production and distribution and share some common but limited resources within the supply chain, whereas the external firms are independent and do not share the internal resources. The supply chain managers strive to develop optimal strategies in terms of production level and resource allocation in maximising their profit while facing competition at the end market. The Cournot–Nash equilibrium of this inter-supply chain competition is formulated as a variational inequality problem. We further study the case when there is demand disruption in the plan-execution phase. In such a case, the managers need to revise their planned strategy in order to maximise their profit with the new demand under disruption and minimise the cost of change. We present a bi-criteria decision-making model for supply chain managers and develop the optimal conditions in equilibrium, which again can be formulated by another variational inequality problem. Numerical examples are presented for illustrative purpose.     

A multi-echelon production–inventory system with supply disruption

The article investigates an integrated multi-layer supply chain model consisting of supplier, manufacturer and retailer while supply disruption, machine breakdown, safety stock, maintenance breakdown occur simultaneously. At beginning of the production, manufacturer keeps some raw materials in stock received from second supplier at high price, as safety stock due to supply disruption of first supplier. Corrective maintenance is done immediately to restore its normal stage when machine breakdown occurs. Stock out situations at manufacturer and retailer are considered due to disruption of production for machine breakdown. The integrated expected costs of the chain in centralized (collaborating) and decentralized (Stakelberg approach) system are compared. A numerical example and its sensitivity analysis are provided to test feasibility of the model.     

Pricing and production decisions in dual-channel supply chains with demand disruptions

This paper develops a two-period pricing and production decision model in a one- manufacturer-one-retailer dual-channel supply chain that experiences a disruption in demand during the planning horizon. While disruption management has long been a key research issue in supply chain management, little attention has been given to disruption management in a dual-channel supply chain once the original production plan has been made. Generally, changes to the original production plan induced by a disruption may impose considerable deviation costs throughout the supply chain system. In this paper, we examine how to adjust the prices and the production plan so that the potential maximal profit is obtained under a disruption scenario. We first study the scenario where the manufacturer and the retailer are vertically integrated with demand disruptions. Then we further assume that the manufacturer bears the deviation costs and obtain the manufacturer’s and the retailer’s individual optimal pricing decision, as well as the manufacturer’s optimal production quantity in a decentralized decision-making setting. We derive conditions under which the maximum profit can be achieved. The results indicate that the optimal production quantity has some robustness under a demand disruption, in both centralized and decentralized dual-channel supply chains. We also find that the optimal pricing decisions are affected by customers’ preference for the direct channel and the market scale change, in both centralized and decentralized dual-channel supply chains.     

Supply chain financing with advance selling under disruption

We study a financing problem in a supply chain (SC) consisting of one supplier and one buyer under supply disruption. The supplier could face a disruption at its end which could effectively reduce its yield in case of disruption, thereby resulting in supply yield uncertainty. The retailer can finance the supplier using advance selling that can help mitigate the impact of disruption. We model this problem as a Stackelberg game, where the supplier as the leader announces the wholesale price and the retailer responds by deciding its optimal order quantity given stochastic demand and an exogenous fixed retail price. The supplier then commences production and a disruption can happen with a known probability. We assume that under disruption the quantity delivered is a fraction of the initial quantity ordered by the retailer. The retailer loses any unmet demand. We analyze three different scenarios of the Stackelberg game, namely no advance selling with disruption, advance selling without disruption, and advance selling with disruption. Our results indicate that advance selling can be used to mitigate the impact of supply disruption and at the same time could lead to an increase in the overall SC profit.     

A reactive mitigation approach for managing supply disruption in a three-tier supply chain

In this paper, we develop a quantitative reactive mitigation approach for managing supply disruption for a supply chain. We consider a three-tier supply chain system with multiple raw material suppliers, a single manufacturer and multiple retailers, where the system may face sudden disruption in its raw material supply. First, we develop a mathematical model that generates a recovery plan after the occurrence of a single disruption. Here, the objective is to minimize the total cost during the recovery time window while being subject to supply, capacity, demand, and delivery constraints. We develop an efficient heuristic to solve the model for a single disruption. Second, we also consider multiple disruptions, where a new disruption may or may not affect the recovery plans of earlier disruptions. We also develop a new dynamic mathematical and heuristic approach that is capable of dealing with multiple disruptions, after the occurrence of each disruption as a series, on a real-time basis. We compare the heuristic solutions with those obtained by a standard search algorithm for a set of randomly generated disruption test problems, which shows the consistent performance of our heuristic. Finally, a simulation model is developed to analyze the effect of randomly generated disruption events that are not known in advance. The numerical results and many random experiments are presented to explain the usefulness of the developed models and methodologies.     

Measuring supply chain resilience using a deterministic modeling approach

To achieve a competitive edge in an uncertain business environment where change is imperative, one of the significant challenges for an organization is to mitigate risk by creating resilient supply chains. This research proposes a model using graph theory which holistically considers all the major enablers of resilience and their interrelationships for analysis using an Interpretive Structural Modeling approach. The uniqueness of this model lies in its ability to quantify resilience by a single numerical index. The quantification of resilience will help organizations assess the effectiveness of various risk mitigation strategies. This will provide tools for managers to compare different supply chains while offering a deeper knowledge of how supply chain characteristics increase or decrease resilience and consequently affect supply chain risk exposure. Thus, the research supports organizations in measuring and analyzing supply chain resilience and facilitates supply chain decision-making. The proposed method could simplify the dynamic nature of environment for managing disruptions in a supply chain. This novel approach for determining the supply chain resilience index (SCRI) advocates the consideration of resilience aspects in supply chain design, thus giving a competitive advantage to achieve market share even during a disruption.