A framework for mapping the RFID-enabled process redesign in a simulation model

Empowered by the possibility to automatically identify unique product instances, the Radio Frequency Identification (RFID) technology is expected to revolutionize the supply chain processes. However, in view of the numerous possible ways that RFID can be implemented within the supply chain, the issue of supporting the design choices based on a credible assessment between the current (as-is) and the future (to-be) processes has become a matter of considerable concern and debate for both practitioners and academics alike. To design RFID implementations in the supply chain using a robust dynamic analysis, we resort to discrete event simulation. As a result, this paper conceptualizes the ‘RFID-enabled process redesign’ and proposes a framework regarding all possible types of RFID effects when integrating the technology within the supply chain processes. The research design was based on the empirical evidence through three case studies combined with the development of simulation models and on theoretical constructs regarding the information technology (IT)-enabled process redesign.     

基于径向基函数神经网络的流程企业供应链预测仿真

本文在比较预测方法的基础上，采用径向基函数（RBF）神经网络技术建立流程企业供应链预测模型，进行了实例预测仿真，并将预测结果与BP网络的预测结果进行了比较。结果表明，RBF网络误差小于BP网络，其中平方根RBF网络的预测仿真误差最小，而BP网络的误差最大。     

基于ANP-灰色聚类方法的供应链风险影响因素研究

供应链网络结构日趋复杂,需要识别供应链网络风险影响因素并对其进行分析．通过分析和识别出供应链运作过程中各种风险影响因素,构建了供应链网络运作风险影响因素评价体系,利用网络分析法对供应链网络风险影响因素和运作阶段进行分析,使用灰色聚类分析对风险因素进行评分,排序并筛选出重要的风险影响因素.通过对汽车零部件供应链网络进行案例分析,得知供应链网络结构特征因素相对于其他因素对供应链网络风险影响程度最大,在供应链管理和研究过程中应对其引起重视.     

考虑政府约束的再制造闭环供应链差别定价博弈模型

本文考虑政府对废弃产品回收的奖惩约束措施,针对一类由制造商、零售商构成的再制造闭环供应链系统,基于博弈论方法研究了新产品和再制造品存在定价差别时集中决策和分散决策模式下的定价策略,得出了闭环供应链成员的最优定价策略和利润,并分析了政府约束措施对闭环供应链运作的影响。研究表明:集中决策下供应链效率高于Stackelberg博弈分散决策,为此设计了一个收益共享协调定价契约实现了闭环供应链的协调,进而分析了政府回收约束情况下再制造过程利润超过制造过程的再制造优先条件。算例分析验证了定价策略及协调机制的有效性。     

价格和服务双因素影响的供应链协调决策模型研究

以单个制造商和存在竞争的两个零售商组成的供应链结构模型为研究对象,建立价格和服务两个重要因素影响的市场需求函数,研究供应链协调决策模型。以销售价格、服务质量和制造商批发价格作为三个决策变量,分析集中决策和分散决策两种情景的最优策略,研究收益共享、服务成本分担、收益共享成本分担等三种不同契约的供应链协调问题,并使用数值仿真方法,分析了相关参数变化对系统协调的影响。仿真结果表明:收益共享契约和成本分担契约需满足一定条件才能达到供应链协调,但其效果不一定实现帕累托最优;收益共享和成本分担契约可实现供应链协调,但收入共享系数需在合理区间取值;改进的收益共享成本分担契约能够避免共享系数的盲区,更加有效地达到供应链协调,保持供应链良好运行。     

Mesoscopic supply chain simulation

This paper reviews and compares existing approaches for supply chain modeling and simulation and applies the mesoscopic modeling and simulation approach using the simulation software MesoSim, an own development. A simplified real-world supply chain example is modeled with discrete event, mesoscopic and system dynamics simulation. The objective of the study is to compare the process of model creation and its validity using each approach. The study examines advantages of the mesoscopic approach for the simulation. Major benefits of the mesoscopic approach are that modeling efforts are balanced with the necessary level of detail and facilitate quick and simple model creation and simulation.     

Feasibility principles for Downstream Demand Inference in supply chains

Many companies are adopting strategies that enable Demand Information Sharing (DIS) between the supply chain links. Recently, a steady stream of research has identified mathematical relationships between demands and orders at any link in the supply chain. Based on these relationships and strict model assumptions, it has been suggested that the upstream member can infer the demand at the downstream member from their orders. If this is so, DIS will be of no value. In this paper, we argue that real-world modelling requires less restrictive assumptions. We present Feasibility Principles to show that it is not possible for an upstream member to accurately infer consumer demand under more realistic model assumptions. Thus, we conclude that DIS has value in supply chains. We then move our focus to the supply chain model assumptions in the papers arguing that there is value in sharing demand information. Using a simulation experiment, we show that the value of sharing demand information in terms of inventory reductions will increase under more realistic supply chain model assumptions.     

低碳供应链协同运作的演化模型

针对低碳供应链协同运作的系统演化问题,运用协同论中的伺服原理分析了低碳供应链中的序参量和运作流程;运用布尔代数的逻辑加和逻辑乘运算规则,分析了序参量和运作流程之间的关系。在此基础上,根据系统动力学中的速率原理,构建了低碳供应链协同运作的演化模型,运用自组织原理分析了序参量影响低碳供应链协同运作的演化过程,运用协同效应原理分析了低碳供应链协同运作规律,并对模型进行了应用仿真分析,得出了低碳供应链协同运作的机理。     

基于博弈视角的中小型供应商联盟决策研究

在绿色供应链管理背景下,中小型供应商在供应链中处于相对弱势的地位,往往在强势的供应链核心企业面前失去定价权;此外,由于其在经济和技术上的双重困难,中小型供应商的生产活动所造成的环境污染日益严重。供应链联盟作为一种新型的企业合作模式,是解决中小型供应商发展问题的有效途径。本文试图构建绿色供应链下的中小型供应商战略联盟博弈模型,并从博弈角度探讨中小型供应商联盟的必要性、可行性以及联盟的最优决策策略,以期探索中小型供应商依托供应链联盟而形成的发展模式。研究结果显示,中小型供应商联盟有利于整体供应链的绿色发展,提升中小型供应商在供应链中的地位。本研究结论能够为绿色供应链中的各方企业提供决策建议。     

Performance metrics in supply chain management

This survey paper starts with a critical analysis of various performance metrics for supply chain management (SCM), used by a specific manufacturing company. Then it summarizes how economic theory treats multiple performance metrics. Actually, the paper proposes to deal with multiple metrics in SCM via the balanced scorecard — which measures customers, internal processes, innovations, and finance. To forecast how the values of these metrics will change — once a supply chain is redesigned — simulation may be used. This paper distinguishes four simulation types for SCM: (i) spreadsheet simulation, (ii) system dynamics, (iii) discrete-event simulation, and (iv) business games. These simulation types may explain the bullwhip effect, predict fill rate values, and educate and train users. Validation of simulation models requires sensitivity analysis; a statistical methodology is proposed. The paper concludes with suggestions for a possible research agenda in SCM. A list with 50 references for further study is included.     

A robust optimization approach to reduce the bullwhip effect of supply chains with vendor order placement lead time delays in an uncertain environment

Supply chain management is important for companies and organizations to improve their business and enhance competitiveness in the global marketplace. The bullwhip effect problem of supply chain systems with vendor order placement lead time delays in an uncertain environment is addressed in this paper. Among the numerous causes of bullwhip effect, we focus on uncertainties with respect to demand, production process, supply chain structure, inventory policy implementation and especially vendor order placement lead time delays. Minimizing the negative effect of these uncertainties in inducing bullwhip effect creates a need for developing dynamical inventory policy that increases responsiveness to demand and decreases volatility in inventory replenishment. First, a dynamic model of supply chain with above uncertainties is developed. Then, a novel uncertainty-dependent robust inventory control method using inventory position information is proposed. Additionally, the maximum allowable vendor order placement lead time delay that ensures the stability of supply chains and the suppression of bullwhip effect under the proposed inventory control policy is explored and measured. We find that vendor order placement lead time delays do play important role in supply chain dynamics and contribute to its turbulence and volatility. The effectiveness and flexibility of proposed method is verified through simulation study.     

Exploring the impacts of radio frequency identification (RFID) technology on supply chain performance

This paper is aimed at providing a framework to help managers of a supply chain enterprise determine the appropriate operational and environmental conditions under which investing in radio frequency identification (RFID) technology is more beneficial. For this purpose, a four-echelon supply chain that is operated under different levels of collaboration is examined in a comprehensive simulation model. Results from the simulation model show that integrating RFID technology within a supply chain provides significantly greater benefits when the level of collaboration between the participants is more intensive. In addition, the results also show that these benefits are stronger when lead times are longer and/or when demand uncertainty in marketplace is lower.     

基于风险管理的动态供应链超网络均衡模型

基于风险管理的动态供应链超网络均衡模型的研究有助于供应链超网络节点厂商在动态环境下优化其风险管理,降低风险损失,提升供应链网络在风险管理下的竞争优势。本文以三层供应链超网络为研究对象,采用风险发生概率和损失函数表达供应链超网络中节点厂商中断风险的特征,构建了基于风险管理的动态供应链超网络均衡模型。模型中包括三种类型的节点,产品生产商、零售商和需求市场,生产商考虑风险损失的情况下,基于动态变化的风险、需求和成本追求个体期望效益最优化。接着,通过进化变分不等式来表达动态供应链超网络风险管理下的均衡解,并采用投影动态系统求解进化变分不等式,通过数值算例验证方法的可靠性和合理性,通过投影动态系统解释某一个厂商趋近均衡解的过程。通过单一厂商趋近均衡解的过程,阐述其他厂商相应的最优决策。     

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.     

Comparing conventional and distributed approaches to simulation in a complex supply-chain health system

Decision making in modern supply chains can be extremely daunting due to their complex nature. Discrete-event simulation is a technique that can support decision making by providing what-if analysis and evaluation of quantitative data. However, modelling supply chain systems can result in massively large and complicated models that can take a very long time to run even with today's powerful desktop computers. Distributed simulation has been suggested as a possible solution to this problem, by enabling the use of multiple computers to run models. To investigate this claim, this paper presents experiences in implementing a simulation model with a ‘conventional’ approach and with a distributed approach. This study takes place in a healthcare setting, the supply chain of blood from donor to recipient. The study compares conventional and distributed model execution times of a supply chain model simulated in the simulation package Simul8. The results show that the execution time of the conventional approach increases almost linearly with the size of the system and also the simulation run period. However, the distributed approach to this problem follows a more linear distribution of the execution time in terms of system size and run time and appears to offer a practical alternative. On the basis of this, the paper concludes that distributed simulation can be successfully applied in certain situations.     

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.     

A transient stochastic simulation–optimization model for operational fuel planning in-theater

Army fuel planners are responsible for developing daily loading plans that specify which tankers to load, with what fuel, and where to send the loaded tankers. The tools used to accomplish this task are custom built spreadsheets which require large amounts of time and effort to use, update, and keep free of errors. This research presents a transient stochastic simulation–optimization model of the in-theater bulk fuel supply chain, where the simulation model is used to simulate the performance of the fuel supply chain under a particular fuel distribution policy and the optimization portion is used to update the policy so that it results in the performance desired by the Army fuel planner. The fuel distribution policy can then be used to derive the daily loading plan. Due to the multi-objective nature of the problem, the set of policies that form the efficient frontier are all candidate policies for the Army fuel planner to select from. Results of experimentation with a wide variety of supply chain scenarios indicate that, for a given supply chain scenario, the optimization portion of the model identifies a set of fuel distribution policies that address the objectives of the Army fuel planner. In addition, the simulation–optimization model comfortably solves the largest supply chain scenarios the Army fuel planner would reasonably be expected to encounter.     

一种特殊的冲击型负荷模型及其供应链可靠度研究

基于一种特殊的单次冲击型负荷模型,对供应链系统受到冲击源N(t)为强度λ的poisson流冲击时的可靠性进行了研究.当冲击间隔小于常数δ时供应链失效,给出了供应链的可靠度函数及数字特征.研究表明可以通过预测该特殊冲击型负荷模型下供应链的期望寿命,做好应急物流保障.     

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.     

Achieving sharp deliveries in supply chains through variance pool allocation

Variability reduction and business process synchronization are acknowledged as key to achieving sharp and timely deliveries in supply chain networks. In this paper, we develop an approach that facilitates variability reduction and business process synchronization for supply chains in a cost effective way. The approach developed is founded on an analogy between mechanical design tolerancing and supply chain lead time compression. We first present a motivating example to describe this analogy. Next, we define, using process capability indices, a new index of delivery performance called delivery sharpness which, when used with the classical performance index delivery probability, measures the accuracy as well as the precision with which products are delivered to the customers. Following this, we solve the following specific problem: how do we compute the allowable variability in lead time for individual stages of the supply chain so that specified levels of delivery sharpness and delivery probability are achieved in a cost-effective way? We call this the variance pool allocation (VPA) problem. We suggest an efficient heuristic approach for solving the VPA problem and also show that a variety of important supply chain design problems can be posed as instances of the VPA problem. One such problem, which is addressed in this paper, is the supply chain partner selection problem. We formulate and solve the VPA problem for a plastics industry supply chain and demonstrate how the solution can be used to choose the best mix of supply chain partners.