Selection of supply portfolio under disruption risks

This paper deals with the optimal selection of supply portfolio in a make-to-order environment in the presence of supply chain disruption risks. Given a set of customer orders for products, the decision maker needs to decide from which supplier to purchase custom parts required for each customer order to minimize total cost and mitigate the impact of disruption risks. The selection of suppliers and allocation of orders is based on price and quality of purchased parts and reliability of delivery. The two types of disruption scenarios are considered: scenarios with independent local disruptions of each supplier and scenarios with local and global disruptions that may result in all suppliers disruption simultaneously. The problem is formulated as a single- or bi-objective mixed integer program and a value-at-risk and conditional value-at-risk approach is applied to control the risk of supply disruptions. The proposed portfolio approach is capable of optimizing the supply portfolio by calculating value-at-risk of cost per part and minimizing expected worst-case cost per part simultaneously. Numerical examples are presented and some computational results are reported.     

Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing

This paper presents a stochastic mixed integer programming approach to integrated supplier selection and customer order scheduling in the presence of supply chain disruption risks, for a single or dual sourcing strategy. The suppliers are assumed to be located in two different geographical regions: in the producer's region (domestic suppliers) and outside the producer's region (foreign suppliers). The supplies are subject to independent random local disruptions that are uniquely associated with a particular supplier and to random semi-global (regional) disruptions that may result in disruption of all suppliers in the same geographical region simultaneously. The domestic suppliers are relatively reliable but more expensive, while the foreign suppliers offer competitive prices, however material flows from these suppliers are more exposed to unexpected disruptions. Given a set of customer orders for products, the decision maker needs to decide which single supplier or which two different suppliers, one from each region, to select for purchasing parts required to complete the customer orders and how to schedule the orders over the planning horizon, to mitigate the impact of disruption risks. The problem objective is either to minimize total cost or to maximize customer service level. The obtained combinatorial stochastic optimization problem will be formulated as a mixed integer program with conditional value-at-risk as a risk measure. The risk-neutral and risk-averse solutions that optimize, respectively average and worst-case performance of a supply chain are compared for a single and dual sourcing strategy and for the two different objective functions. Numerical examples and computational results are presented and some managerial insights on the choice between the two sourcing strategies are reported.     

On the fair optimization of cost and customer service level in a supply chain under disruption risks

This paper presents a new decision-making problem of a fair optimization with respect to the two equally important conflicting objective functions: cost and customer service level, in the presence of supply chain disruption risks. Given a set of customer orders for products, the decision maker needs to select suppliers of parts required to complete the orders, allocate the demand for parts among the selected suppliers, and schedule the orders over the planning horizon, to equitably optimize expected cost and expected customer service level. The supplies of parts are subject to independent random local and regional disruptions. The fair decision-making aims at achieving the normalized expected cost and customer service level values as much close to each other as possible. The obtained combinatorial stochastic optimization problem is formulated as a stochastic mixed integer program with the ordered weighted averaging aggregation of the two conflicting objective functions. Numerical examples and computational results, in particular comparison with the weighted-sum aggregation of the two objective functions are presented and some managerial insights are reported. The findings indicate that for the minimum cost objective the cheapest supplier is usually selected, and for the maximum service level objective a subset of most reliable and most expensive suppliers is usually chosen, whereas the equitably efficient supply portfolio usually combines the most reliable and the cheapest suppliers. While the minimum cost objective function leads to the largest expected unfulfilled demand and the expected production schedule for the maximum service level follows the customer demand with the smallest expected unfulfilled demand, the equitably efficient solution ensures a reasonable value of expected unfulfilled demand.     

An integrated supplier selection and inventory problem with multi-sourcing and lateral transshipments

In this research, we consider the supplier selection problem of a firm offering a single product via multiple warehouses. The warehouses face stationary, stochastic demand and replenish their inventory via multiple suppliers, to be determined from a set of candidates, with varying price, capacity, quality, and disruption characteristics. Additionally, the warehouses may simultaneously replenish their inventory from other warehouses proactively. With these characteristics, the problem is a multi-sourcing, supplier selection, and inventory problem with lateral transshipments. Even though the benefits of multi-sourcing and lateral transshipments have been presented in the literature individually to mitigate risks associated with uncertain demand and disrupted supply, the intertwined sourcing and inventory decisions under these settings have not been investigated from a quantitative perspective. We develop a decomposition based heuristic algorithm, powered with simulation. While the decomposition based heuristic determines a solution with supplier selection and inventory decisions, the simulation model evaluates the objective function value corresponding to each generated solution. Experimental results show, contrary to the existing literature, inferior decisions may result when considering the selection of suppliers solely on unit and/or contractual costs. We also evaluate the impact of multi-sourcing with rare but long disruptions compared to frequent but short ones.     

需求和生产成本同时扰动下供应链期权契约应对突发事件

本文研究了单一供应商和单一零售商组成的供应链在期权契约下的应急协调问题。首先证明了稳定条件下的期权契约能够实现该供应链的协调,当突发事件导致随机市场需求分布函数和制造商生产成本同时扰动时,在市场需求和生产成本变化满足一定条件下,供应链最优购买量不变,否则将会发生改变,此时协调被打破;通过调整期权契约能够实现对突发事件的协调应对。最后运用数值实验对模型进行了验证。     

考虑供应风险的多源应急物资采购双层规划模型

自然灾害频繁发生,事故灾难不断涌现,公共卫生事件猝不及防,社会安全风险交织叠加,给人们的生产和生活带来了巨大的风险和不确定性。在突发事件背景下,考虑应急物资供应中的各类风险,激励多源应急物资的稳定供给,受到党和政府高度重视。应急物资供应有哪些风险,如何规避这些风险,针对多种渠道的采购,如何优化采购结构。这些问题是本论文关注的重点。本文以政府、制造型企业、受灾地区民众为决策主体的三级供应链为基础,构建了上层以整个供应链系统收益最大化为目标函数、下层以供应风险最小化为目标函数的双层规划模型,对不同情景下物资采购订单的分配进行研究。在此基础上,本文以某市洪涝灾害为例进行分析,证明了模型的可行性,并探究了供应风险变化对物资采购订单分配、以及整个供应链系统收益的影响,以期为政府应急物资采购决策提供参考性建议。     

Managing Supply Disruptions when Sourcing from Reliable and Unreliable Suppliers

We study a manufacturer's optimal multiple‐sourcing strategies when some but not all suppliers face risks of complete supply disruptions. Using an approximate model, we show that the optimal unreliable orders are ranked by a simple and intuitive criterion, and are invariant of minor market size changes. Furthermore, when ordering from one reliable and one unreliable supplier, we show that the total order quantity and its allocation between the two suppliers are independent decisions. We then test and confirm the robustness of the insights without the approximation, as well as when we relax various assumptions.     

Price competition,cost and demand disruptions and coordination of a supply chain with one manufacturer and two competing retailers

This paper studies the coordination of a supply chain with one manufacturer and two competing retailers after the production cost of the manufacturer was disrupted. We consider two coordination mechanisms: an all-unit quantity discount and an incremental quantity discount. For each mechanism, we develop the conditions under which the supply chain is coordinated and discuss how the cost disruption may affect the coordination mechanisms. For the all-unit quantity discount scheme, we find that the manufacturer charges the lower-cost retailer for a lower unit wholesale price in order to induce him to order more products. If the costs of two retailers have a remarkable difference, then the all-unit quantity discount scheme cannot coordinate the supply chain with disruptions. While the cost disruption may affect the wholesale prices, order quantities as well as retail prices, it is optimal for the supply chain to keep the original coordination mechanism if the production cost change is sufficiently small. The model is also extended to the case with both cost and demand disruptions. The equilibrium strategies of the retailers are investigated when the manufacturer cannot timely react to the disruptions such that she has to keep the original mechanism. We illustrate the results by numerical examples.     

供应商产出随机与供应中断下的双源采购决策

研究在需求与供应不确定条件下,一个制造商向两个存在产出随机和供应中断可能性的供应商采购零部件时的最优决策问题。论文分别针对两种情况：（1）只考虑供应商产出随机,（2）同时考虑供应商产出随机与供应中断可能性,建立了两种情况下制造商与两个供应商之间的博弈模型,证明了在两种情况下,制造商均存在最优订货量、供应商存在最优生产量使自身利润最优。研究发现,供应商产出稳定性的改善（即产出随机性降低）不仅可以使自身获得更大的利润,也使制造商获得更大的利润。供应商最优生产量随着自身产出随机性降低先增后减。同时,供应商供应中断可能性的降低会为自身带来更大的收益,也为制造商带来更大的收益。     

非对称信息下闭环供应链回购契约应对突发事件策略研究

研究了非对称信息下一个制造商和一个零售商组成的两级闭环供应链在回购契约下的协调问题。在考虑零售商销售成本信息为非对称信息和随机性市场需求基础上,首先,分析了在正常状态下分散式系统决策情况,通过重新设计可变参数解决了信息不对称的问题,实现了回购契约下的信息共享和供应链的完美协调;然后,探讨了闭环供应链回购契约应对突发事件的协调问题。研究结果表明：当突发事件造成市场规模和制造商生产成本同时扰动时,闭环供应链的销售活动将受影响,闭环供应链的协调将被打破,而闭环供应链的废旧品回收活动却不受突发事件的影响。为此,给出了闭环供应链回购契约的应急决策。最后通过数值算例验证了结论。     

Dual Sourcing Under Random Supply Capacities: The Role of the Slow Supplier

Sourcing from multiple suppliers with different characteristics is common in practice for various reasons. This paper studies a dynamic procurement planning problem in which the firm can replenish inventory from a fast and a slow supplier, both with uncertain capacities. The optimal policy is characterized by two reorder points, one for each supplier. Whenever the pre‐order inventory level is below the reorder point, a replenishment order is issued to the corresponding supplier. Interestingly, the reorder point for the slow supplier can be higher than that of the fast even if the former has a higher cost, lower reliability, and smaller capacity than the latter, suggesting the possibility of ordering exclusively from an inferior slow supplier in the short term. Moreover, the firm may allocate a larger portion of the long‐term total order quantity to the slow supplier than to the fast, even if the former does not possess any cost or reliability advantage over the latter. Such phenomena, different from the observations made in previous studies, happen when the demand is uncertain and the supply is limited or unreliable. Our observations highlight the importance of incorporating both demand uncertainty and supplier characteristics (i.e., cost, lead time, capacity and uncertainty) in a unified framework when formulating supplier selection and order allocation strategies.     

多零售商供应链应对突发事件的协调机制研究

本文针对一个供应商和n个Cournot竞争零售商组成的供应链系统,从系统优化和企业管理的角度研究了该供应链系统如何应对突发事件。首先证明稳定条件下的收益共享合约能实现该供应链协调。但突发事件引起的成本和需求的扰动会打破供应链协调,当突发事件导致供应链的市场需求增加而生产成本减少时,供应商必须通过增加生产来应对突发事件;当突发事件导致供应链的市场需求减少而生产成本增加时,供应商必须通过减少生产来应对突发事件;并通过求解突发事件下供应链系统最优利润的Karush-Kuhn-Tucker(KKT)条件,提出了供应链在一体化时应对突发事件的最优策略。进一步证明了改进的收益共享合约可以协调突发事件下分散化决策的供应链系统。最后运用数值实验对模型进行了验证。     

A sustainable supply chain network considering lot sizing with quantity discounts under disruption risks: centralized and decentralized models

This study proposes a framework for the main parties of a sustainable supply chain network considering lot-sizing impact with quantity discounts under disruption risk among the first studies. The proposed problem differs from most studies considering supplier selection and order allocation in this area. First, regarding the concept of the triple bottom line, total cost, environmental emissions, and job opportunities are considered to cover the criteria of sustainability. Second, the application of this supply chain network is transformer production. Third, applying an economic order quantity model lets our model have a smart inventory plan to control the uncertainties. Most significantly, we present both centralized and decentralized optimization models to cope with the considered problem. The proposed centralized model focuses on pricing and inventory decisions of a supply chain network with a focus on supplier selection and order allocation parts. This model is formulated by a scenario-based stochastic mixed-integer non-linear programming approach. Our second model focuses on the competition of suppliers based on the price of products with regard to sustainability. In this regard, a Stackelberg game model is developed. Based on this comparison, we can see that the sum of the costs for both levels is lower than the cost without the bi-level approach. However, the computational time for the bi-level approach is more than for the centralized model. This means that the proposed optimization model can better solve our problem to achieve a better solution than the centralized optimization model. However, obtaining this better answer also requires more processing time. To address both optimization models, a hybrid bio-inspired metaheuristic as the hybrid of imperialist competitive algorithm (ICA) and particle swarm optimization (PSO) is utilized. The proposed algorithm is compared with its individuals. All employed optimizers have been tuned by the Taguchi method and validated by an exact solver in small sizes. Numerical results show that striking similarities are observed between the results of the algorithms, but the standard deviations of PSO and ICA–PSO show better behavior. Furthermore, while PSO consumes less time among the metaheuristics, the proposed hybrid metaheuristic named ICA–PSO shows more time computations in all small instances. Finally, the provided results confirm the efficiency and the performance of the proposed framework and the proposed hybrid metaheuristic algorithm.

     

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。     

两级供应链中供应中断情形下零售商转运策略

考虑由两个供应商和两个零售商组成的两级供应链系统,且两个供应商以一定概率发生供货中断,基于供应商供货发生中断的四种情形,分别对零售商实施相互转运策略、单向转运策略和不转运策略下建立最优订货决策模型。从理论上比较了三种策略下零售商期望利润和订货量高低,并分析相互转运和单向转运策略下零售商期望利润和订货量与转运价格、转运成本之间的关系,最后运用算例进行验证,同时分析了三种策略下,供应中断概率和其它主要参数的变化对零售商期望利润和最优订货量的影响。     

基于EOQ的集成供应成本分摊问题研究

第三方物流的集成供应是降低供应链成本的有效途径,而集成供应成本在各供应商企业之间的分摊是需要解决的核心问题.本文详细阐述了第三方物流的集成供应问题,基于合作博弈理论建立了第三方物流集成供应的成本分摊模型.在采用夏普利值法对该模型进行求解的过程中,针对夏普利值法难以赋值的问题,引入集成供应的经济订货批量模型,有效解决了了第三方物流供应成本分摊问题.最后,用算例对该方法进行了说明.     

Integrated supply,production and distribution scheduling under disruption risks

This paper presents a bi-objective stochastic mixed integer programming approach for a joint selection of suppliers and scheduling of production and distribution in a multi-echelon supply chain subject to local and regional disruption risks. Two conflicting problem objectives are minimization of cost and maximization of service level. The three shipping methods are considered for distribution of products: batch shipping with a single shipment of different customer orders, batch shipping with multiple shipments of different customer orders and individual shipping of each customer order immediately after its completion. The stochastic combinatorial optimization problem is formulated as a time-indexed mixed integer program with the weighted-sum aggregation of the two objective functions. The supply portfolio is determined by binary selection and fractional allocation variables while time-indexed assignment variables determine the production and distribution schedules. The problem formulation incorporates supply–production, production–distribution and supply–distribution coordinating constraints to efficiently coordinate supply, production and distribution schedules. Numerical examples modelled after an electronics supply chain and computational results are presented and some managerial insights are reported. The findings indicate that for all shipping methods, the service-oriented supply portfolio is more diversified than the cost-oriented portfolio and the more cost-oriented decision-making, the more delayed the expected supply, production and distribution schedules.     

供应链应急援助的CVaR模型

企业间通过应急援助方式共同应对突发事件是供应链应急管理的常用合作策略,而应急合作目标是防止突发事件下的损失失去控制.本文引入CVaR来刻画企业在突发事件下的应急目标,进而建立供应链应急援助的决策模型,分析了供应商和零售商遭遇突发事件时的应急援助状况并给出了在一定置信水平控制下的最优援助额.研究表明:CVaR方法能够恰当...     

考虑不同碳排放处理模式的动态供应商选择及采购批量问题研究

不同的碳排放处理模式及不确定的市场需求等因素影响下,如何选择供应商并确定采购批量直接影响企业的运营和效益。本文在多时间周期、多产品种类、多供应商及随机需求情形下,同时考虑不同碳排放处理模式,分析动态供应商选择及采购批量等最优决策问题,构建混合整数非线性规划模型。通过设计变异算子和扰动因子来改进粒子群算法,力求在短时间内求解大规模决策问题。针对不同规模供应商选择及采购批量决策问题,采用精确方法、近似方法和改进粒子群算法求解。数值实验验证了模型及改进粒子群算法的有效性和可行性,分析了碳税、碳交易价格及碳限额对供应链管理的影响,并给出了供应商选择及碳排放处理的决策参考建议。     

时间约束下不对称信息鲜活农产品供应链应对突发事件协调模型

针对一个由供应商和一个零售商构成的鲜活农产品供应链,在考虑损耗和新鲜度的影响下,假设产品的市场需求为零售价格的非线性函数,零售商成本为私有信息,研究如何协调供应链应对突发事件。 首先,给出了对称信息下供应链协调模型;然后,研究了不对称信息下集权式与分权式供应链的协调机制;再次,研究了在突发事件引起零售商成本分布函数扰动情况下,供应链的最优应对策略。 研究表明,供应链的最优生产计划、最优批发价格和最优零售价格均具有一定的鲁棒性,当突发事件造成零售商期望成本在一定范围内发生扰动时,三者可以保持不变。最后,通过数值仿真验证了相关结论。