Supply chain design under uncertainty using sample average approximation and dual decomposition

We present a supply chain design problem modeled as a sequence of splitting and combining processes. We formulate the problem as a two-stage stochastic program. The first-stage decisions are strategic location decisions, whereas the second stage consists of operational decisions. The objective is to minimize the sum of investment costs and expected costs of operating the supply chain. In particular the model emphasizes the importance of operational flexibility when making strategic decisions. For that reason short-term uncertainty is considered as well as long-term uncertainty. The real-world case used to illustrate the model is from the Norwegian meat industry. We solve the problem by sample average approximation in combination with dual decomposition. Computational results are presented for different sample sizes and different levels of data aggregation in the second stage.     

A flexible and generic approach to dynamic modelling of supply chains

In this paper, we present a new modelling approach for realistic supply chain simulation. The model provides an experimental environment for informed comparison between different supply chain policies. A basic simulation model for a generic node, from which a supply chain network can be built, has been developed using an object-oriented approach. This generic model allows the incorporation of the information and physical systems and decision-making policies used by each node. The object-oriented approach gives the flexibility in specifying the supply chain configuration and operation decisions, and policies. Stochastic simulations are achieved by applying Latin Supercube Sampling to the uncertain variables in descending order of importance, which reduces the number of simulations required. We also present a case study to show that the model is applicable to a real-life situation for dynamic stochastic studies.     

三级供应链企业间交叉持股时均衡定价及市场绩效研究

本文构建三级供应链企业间纵向交叉持股时的Stackelberg定价博弈模型,采用逆推归纳法推演出供应链各厂商交叉持股时的均衡定价及其利润公式,分析了交叉持股对三级供应链均衡市场价格、厂商利润、消费者剩余和经济福利的影响。研究结果表明,较之无交叉持股,仅下游厂商对上游厂商单向持股,对供应链的绩效没有影响;而适当增大上游厂商对下游厂商持股,限制下游厂商对上游厂商持股,能有效降低市场价格,提高供应链及各厂商的利润,增加消费者剩余,改善经济福利,实现供应链各厂商与消费者的共赢。     

Supply chain performance evaluation with data envelopment analysis and balanced scorecard approach

One of the most complicated decision making problems for managers is the evaluation of supply chain (SC) performance which involves various criteria. Though vast studies have been recorded on supply chain efficiency evaluation via balanced scorecard (BSC) approach, these studies do not focus on the relationships between the four perspectives of BSC approach. The present paper is an attempt focusing on these relationships, especially the returnable ones. To do so, at first, all relationships between the four perspectives of BSC were determined and then the DEMATEL approach was employed to obtain a network structure. This network structure was then used to create a network DEA model. Since it was not possible to calculate the efficiency evaluation score by BSC, the data envelopment analysis (DEA) model was used for such an evaluation. Moreover, after reviewing different tools to evaluate the performance of supply chain, a new approach, relying on network DEA with BSC approach, was generated. Finally, this model was applied in the Iranian food industry to evaluate its supply chains efficiency and the results proved the high efficiency of the model designed. The findings could be used in various evaluation processes in different industries.     

Interactive group decision-making using a fuzzy linguistic approach for evaluating the flexibility in a supply chain

With global competition rapidly intensifying and shifting to the supply chain level, the supply chain flexibility has become increasingly important. However, the literature addressing supply chain flexibility remains limited. This study thus builds a group decision-making structure model of flexibility in supply chain management development. This study presents a framework for evaluating supply chain flexibility comprising two parts, an evaluation hierarchy with flexibility dimensions and related metrics, and an evaluation scheme that uses a three-stage process to evaluate supply chain flexibility. This study then proposes an algorithm for determining the degree of supply chain flexibility using a fuzzy linguistic approach. Evaluations of the degree of supply chain flexibility can identify the need to improve supply chain flexibility, and identify specific dimensions of supply chain flexibility as the best directions for improvement. The results of this study are more objective and unbiased for two reasons. First, the results are generated by group decision-making with interactive consensus analysis. Second, the fuzzy linguistic approach used in this study has more advantage to preserve no loss of information than other methods. Additionally, this study presents an example using a case study to illustrate the availability of the proposed methods and compare it with other methods.     

The impact of forecasting model selection on the value of information sharing in a supply chain

This paper presents a study on the impact of forecasting model selection on the value of information sharing in a supply chain with one capacitated supplier and multiple retailers. Using a computer simulation model, this study examines demand forecasting and inventory replenishment decisions by the retailers, and production decisions by the supplier under different demand patterns and capacity tightness. Analyses of the simulation output indicate that the selection of the forecasting model significantly influences the performance of the supply chain and the value of information sharing. Furthermore, demand patterns faced by retailers and capacity tightness faced by the supplier also significantly influence the value of information sharing. The result also shows that substantial cost savings can be realized through information sharing and thus help to motivate trading partners to share information in the supply chain. The findings can also help supply chain managers select suitable forecasting models to improve supply chain performance.     

信息共享程度对我国服装供应链库存成本的影响

我国服装行业库存水平近年逐渐恶化,库存问题成为该行业发展的重要瓶颈。信息共享被认为是有效解决该问题的方法之一。然而目前国内文献对我国服装行业信息共享的定量研究较为缺乏;同时国内外对信息共享的普适研究也多集中于比较共享与不共享信息的影响,鲜有文章研究信息共享程度对供应链绩效的影响。本文通过建立信息共享量化模型分析以下三种情况对服装行业供应商库存水平及成本的影响:(1)共享需求统计信息,(2)共享实时需求信息,(3)共享需求及市场信息。本文研究表明,共享实时需求信息比共享需求统计信息能有效降低供应商库存水平及成本;而额外共享市场信息,能增加供应链柔性,提高其应对市场不确定性的能力。本文研究信息共享程度对服装行业供应链的影响,旨在降低我国服装供应链高库存水平,并为我国服装企业信息化及品牌建设提供管理启示。     

零售与回收双竞争环境下闭环供应链线性转移支付契约研究

利用博弈理论研究了由单个制造商与n个零售商组成的零售与回收均存在竞争的闭环供应链的协调问题,给出了分散决策与集中决策情形下系统成员的最优决策和收益,发现分散决策使闭环供应链系统收益受损;提出了一种线性转移支付契约,实现了闭环供应链的协调.最后,通过一个数值算例验证了研究结论.     

A model for supply chain design considering the cost of quality

Recent studies have shown that the cost of quality (COQ) is of more strategic and economic importance than previously conceived. Whereas previous works have applied COQ as an internal performance measure within companies, the purpose of this paper is to present a model for supply chain design that computes the COQ as a global performance measure for the entire supply chain. In addition, rather than assume an exogenously given COQ curve, our model computes COQ in terms of internal operational decisions such as the error rate at inspection and fraction defective at manufacturing. The model can be used to design a logistic route that achieves a minimum total cost while maintaining an overall quality level and to evaluate the impact of investment in quality to increase overall profits. The behaviour of the model is illustrated with numerical examples that show how the COQ function changes depending on various parameters.     

A multi-objective approach to supply chain visibility and risk

This paper investigates the twin effects of supply chain visibility (SCV) and supply chain risk (SCR) on supply chain performance. Operationally, SCV has been linked to the capability of sharing timely and accurate information on exogenous demand, quantity and location of inventory, transport related cost, and other logistics activities throughout an entire supply chain. Similarly, SCR can be viewed as the likelihood that an adverse event has occurred during a certain epoch within a supply chain and the associated consequences of that event which affects supply chain performance. Given the multi-faceted attributes of the decision making process which involves many stages, objectives, and stakeholders, it beckons research into this aspect of the supply chain to utilize a fuzzy multi-objective decision making approach to model SCV and SCR from an operational perspective. Hence, our model incorporates the objectives of SCV maximization, SCR minimization, and cost minimization under the constraints of budget, customer demand, production capacity, and supply availability. A numerical example is used to demonstrate the applicability of the model. Our results suggest that decision makers tend to mitigate SCR first then enhance SCV.     

Modelling decision behaviours in pricing game of closed-loop supply chains

This paper experimentally and analytically studies pricing decisions in closed-loop supply chains. Experimental results show considerable deviations from theoretical predictions by traditional pricing models. Moreover, social relationships can affect decision results, and double marginalization is reduced in closed-loop supply chains. For in-depth analysis of experimental results, we further extended the quantal response equilibrium model by incorporating the fairness concerns of both the manufacturer and retailer. The analysis results of the developed model suggest that participants exhibit bounded rationality and fairness concerns when they make decisions. Social relationships can also influence the degree of fairness concerns.     

Capacity augmentation of a supply chain for a short lifecycle product: A system dynamics framework

For an innovative product characterized by short product lifecycle and high demand uncertainty, investment in capacity buildup has to be done cautiously. Otherwise either the product’s market diffusion is impeded or the manufacturer is left with unutilized capacity. Using the right information for making capacity augmentation decisions is critical in facing this challenge. In this paper, we propose a method for identifying critical information flows using the system dynamics model of a two-echelon supply chain. The fundamental premise of system dynamics methodology is that (system) structure determines (its) behavior. Using loop dominance analysis method we study the feedback loop structure of the supply chain system. The outcome is a set of dominant loops that determine the dynamics of capacity growth. It is revealed that the delivery delay information has little effect while the loop that connects retail sales with production order affects the dynamics significantly. Modifying this loop yields appropriate capacity augmentation decisions resulting in higher performance. What-if analyses bring out effects of modifying other structural elements. In conclusion, we claim that the information feedback based methodology is general enough to be useful in designing decision support systems for capacity augmentation. The limitations of the model are also discussed and possible extensions identified.     

Multiobjective vendor allocation in multiechelon inventory systems: a spreadsheet model

The vendor selection problem (VSP) is a critical element of the numerous managerial decisions in the consideration of both outsourcing and integrated supply chain management. Many papers in the literature have dealt with VSPs from a multicriteria perspective, but few have looked into the implications of such decisions in a multiechelon supply chain with the explicit consideration of multiple time-phased demands. A new integrated supply chain model is proposed for a multiechelon supply chain. This model takes into account the usual cost objective and other important criteria in a multiechelon supply chain ranging from the most upstream suppliers' quality to end customers' satisfaction level through a large-scale multiobjective linear programme (MOLP). Furthermore, various Pareto optimal solutions can be graphically presented to facilitate decision making and negotiations with existing and potential suppliers.     

Random yield supply chain with a yield dependent secondary market

This paper considers a simple supply chain with one supplier and one retailer where the supplier’s production is subject to random yield and the retailer faces uncertain demand. There exists a secondary market for acquiring or disposing products by the supplier. We study both the centralized and decentralized systems. In the decentralized system, a no risk sharing contract and a risk sharing minimum commitment contract are analyzed. The supply chain with the risk sharing contract is further analyzed with a constant secondary market price and a yield dependent secondary market price. We present both the supplier’s and the retailer’s optimal strategies and provide insights for managers when making decisions under random yield risk and demand uncertainty. We find that the secondary market generally has a positive impact on supply chain performance and the actual effect of random yield risk on the supply chain performance depends on cost parameters and supply chain contract settings. Under certain conditions, reducing yield randomness may weaken the double marginalization effect and improve the chain performance. From the numerical study, we also show that there exists an optimal commitment level for the supply chain.     

The efficiency of joint decision making in buyer-supplier relationships

This paper examines the effectiveness of joint decision making within 87 pairs of buyer-supplier relationships in manufacturing. Joint decision making is an important attribute of a more cooperative supply chain relationship that may ultimately result in a better performance. Efficiency is modeled as a multiple criteria problem using Data Envelopment Analysis (DEA). Inputs of five kinds of joint decision making activity are examined relative to two measures of output based on the assessment of the buying firm. Three contingent constructs (product customization and innovation, media richness of the communication between buyer and supplier, and continuity in the relationship) are then examined for their impact on the relative performance of each pair. The implications for the management of supply chain relationships and benchmarking of best practice are then discussed.     

Towards a multi-objective performance assessment and optimization model of a two-echelon supply chain using SCOR metrics

This paper aims at multi-objective performance assessment and optimization of a multi-period two-echelon supply chain consisting of a supplier and a manufacturer. On the basis of the assessment system of the supply-chain operations reference model, the supply chain’s performance is investigated with respect to costs, assets, agility, reliability and responsiveness. First, methods to quantify these five performance attributes are put forward. Then a multi-objective mathematical programming model is developed for production decision making of components and products so that the supply chain’s performance frontier formed with Pareto efficient performance values can be achieved. Thereafter a simple augmented \(\epsilon \) -constraint method is proposed for searching for all Pareto efficient solutions of the multi-objective mathematical programming problem. Finally, efficiency of the method is demonstrated with a numerical example and a sensitivity analysis is implemented to reveal effects of capacity expansion on supply chains’ performance.     

随机弹性需求下供应链销售价格与提前期联合决策及协调机制

研究了市场需求随机且对销售价格及提前期敏感的条件下,供应链如何制定最优的销售价格、提前期以及库存因子使得利润最大化。首先,分析了集中决策与分散决策供应链的最优决策,发现集中决策与分散决策模式下的提前期与库存因子是相同的,但分散决策下的销售价格更高、期望利润更低,且分散决策与集中决策供应链的利润之比随着需求对价格的敏感程度的增大而增大。然后建立了收入共享与成本分担的协调机制,并分析了其最优决策。研究发现,协调决策机制可以有效地压缩提前期,并能同时使供应链达到帕累托改进,但不能达到完美协调,而且还发现协调决策下制定的最优销售价格比分散决策要低。最后通过数值计算对三种供应链决策模式下的绩效进行了比较分析,结果表明供应链利润随着需求方差增大而减小,提前期压缩程度随着材料成本承担比例增大而增大。上述结论可以为企业制定销售价格与提前期决策以及企业间的协调提供有益的指导。     

An integrated optimization model for managing the global value chain of a chemical commodities manufacturer

The realization of supply chain management concepts goes along with the introduction of comprehensive software systems for supporting decisions at the strategic, tactical, and operational planning level. Moreover, in industry the focus has shifted from a pure logistics-oriented view towards the integration of pricing and revenue issues into cross-functional value chain planning models. This paper presents a practical decision support tool for global value chain planning in the production of chemical commodities. The proposed linear optimization model consists of various modules that reflect sales, distribution, production, and procurement activities within a company-internal value chain. The objective of the model is to maximize profit by coordinating all activities within the supply chain. The model formulation is related to a real industry case. It is shown how the model can be used to support decision making from sales to procurement by volume and value.     

Supply chain DEA: production possibility set and performance evaluation model

Performance evaluation is of great importance for effective supply chain management. The foundation of efficiency evaluation is to faithfully identify the corresponding production possibility set. Although a lot of researches have been done on supply chain DEA models, the exact definition for supply chain production possibility set is still in absence. This paper defines two types of supply chain production possibility sets, which are proved to be equivalent to each other. Based upon the production possibility set, a supply chain CRS DEA model is advanced to appraise the overall technical efficiency of supply chains. The major advantage of the model lies on the fact that it can help to find out the most efficient production abilities in supply chains, by replacing or improving inefficient subsystems (supply chain members). The proposed model also directly identifies the benchmarking units for inefficient supply chains to improve their performance. A real case validates the reasonableness and acceptability of this approach.     

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.