一种新的灰色预测模型及其建模机理

为了提高灰色模型的预测精度,并拓展其应用范围,针对具有近似非齐次指数律特征的数据序列,构建了一种新的灰色预测模型ＮＧＭ（１,１,k）．通过最小二乘法求出了新灰色模型参数的计算公式,以微分方程作为演绎推理工具,得到了该模型的时间响应序列函数,并对其建模精度进行了理论和实验分析．研究结果表明了所提出的灰色模型的有效性和适用性．     

A time staged linear programming model for production loading problems with import quota limit in a global supply chain

Globalization has ushered in a new era when more and more companies are expanding their manufacturing operations on a global scale. This poses some special challenges and raises certain issues. This paper examines production loading problems that involve import quota limits in the global supply chain network. Import quota, which is imposed by importing countries (mostly in North America and Europe), requires that certain types of products imported into these countries are against valid quotas held by the exporters. Globally loading of production, therefore, requires new methods and techniques, which are different from those used in domestic loading of production. This paper presents a time staged linear programming model for production loading problems with import limits to minimize the total cost, consisting of raw materials cost, machine cost, labour cost, overtime cost, inventory cost, outsourcing cost and quota related costs. To enhance the practical implications of the proposed model, different managerial production loading plans are evaluated according to expected changes in future production policies and situations. A series of computational results demonstrate the effectiveness of the proposed model.     

基于制造商促销的供应链战略库存协调模型

考虑由单个制造商和单个零售商组成的两周期供应链系统,在第一周期结束后零售商储存战略库存控制第二周期制造商批发价格的活动条件下,分别建立了集中式决策、分散式决策以及制造商促销的契约决策的供应链模型,并对三种情况下的决策变量进行了比较分析。研究结果表明：在零售商主导的情境下,零售商没有必要储存战略库存;在制造商主导的情境下,制造商通过简单的批发价格契约无法促进渠道的协调,而在制造商进行促销决策条件下,零售商的战略库存量减少,且制造商和零售商的最优利润均大于分散式决策时的最优利润。最后通过算例验证该模型的有效性。     

A global supply chain risk management framework: An application of text-mining to identify region-specific supply chain risks

Nowadays global supply chains enable companies to enhance competitive advantages, increase manufacturing flexibility and reduce costs through a broader selection of suppliers. Despite these benefits, however, insufficient understanding of uncertain regional differences and changes often increases risks in supply chain operations and even leads to a complete disruption of a supply chain. This paper addresses this issue by proposing a text-mining based global supply chain risk management framework involving two phases. First, the extant literature about global supply chain risks was collected and analyzed using a text-based approaches, including term frequency, correlation, and bi-gram analysis. The results of these analyses revealed whether the term-related content is important in the studied literature, and correlated topic model clustering further assisted in defining potential supply chain risk factors. A risk categorization (hierarchy) containing a total of seven global supply chain risk types and underlying risk factors was developed based on the results. In the second phase, utilizing these risk factors, sentiment analysis was conducted on online news articles, selected according to the specific type of risk, to recognize the pattern of risk variation. The risk hierarchy and sentiment analysis results can improve the understanding of regional global supply chain risks and provide guidance in supplier selection.     

A new forecasting scheme for evaluating long‐term prediction performances in supply chain management

Supply chain management (SCM) practitioners in inventory sites are often required to predict the future sales of products in order to meet customer demands and reduce inventory costs simultaneously. Although a variety of forecasting methods have been developed, many of them may not be used in practice for various reasons, such as insufficient viable information about sales and oversophisticated methods. In this paper, we provide a new forecasting scheme to evaluate long‐term prediction performances in SCM. Three well‐known forecasting methods for time series data—moving average (MA), autoregressive integrated MA, and smoothing spline—are considered. We also focus on two representative sales patterns, each of which is with and without a growth pattern, respectively. By applying the proposed scheme to various simulated and real datasets, this research aims to provide SCM practitioners with a general guideline for time series sales forecasting, so that they can easily understand what prediction performance measures and which forecasting method can be considered.     

闭环供应链混合切换库存控制模型研究

针对一类具有回收、再制造、再分销的闭环供应链系统,以再制造产品的补货能力为切换信号设计了基于再制造优先的混合切换库存控制策略,使得市场需求优先由再制造产品满足,并应用切换控制理论研究混合切换库存控制策略的性能特征,分析系统参数对闭环供应链系统的关键性能指标的影响。仿真分析表明,合理的切换控制策略可以有效抑制闭环供应链运作过程的波动,保证系统具有良好的“牛鞭效应”特征、平稳的库存管理成本以及较高的顾客服务水平。     

Key performance indicators for the evaluation of RFID-enabled B-to-B e-commerce applications: the case of a five-layer supply chain

This paper attempts to track key performance indicators in order to assess the impacts of RFID technology in a five layer supply chain in the utility sector. Findings point to some performance improvements especially when RFID enables more integrated and more collaborative B-to-B e-commerce solutions. The research design involves multiple units and levels of analysis, and relies on diverse data collection methods and generates a vast amount of data. The concept of a living laboratory proved to be an insightful approach for exploring issues related to inter-company connectedness and relationship management. An earlier version of this paper was published in the proceedings of the 40th Hawaii International Conference on System Sciences (HICSS-40).     

基于深度学习的集群式供应链应急物资需求预测研究

在突发事件和大数据情景下,建立基于数据流模糊C均值聚类算法的集群式供应链应急物资需求重要度决策算法,有助于辨识集群式供应链子系统应急物资需求的重要程度。针对集群式供应链中各子供应链之间的耦合特性和预测指标的快速变化数据流特征,提出基于长短期记忆网络的集群式供应链应急物资需求动态预测算法,提取集群式供应链多个子系统应急物资需求参数的时序特征,动态地、分布地对互联大系统的应急物资需求不确定性进行系统辨识估计。仿真实验结果表明了基于长短期记忆网络的集群式供应链互联大系统应急物资需求动态预测算法的可行性和精确性。     

A computerized causal forecasting system using genetic algorithms in supply chain management

Forecasting activities are widely performed in the various areas of supply chains for predicting important supply chain management (SCM) measurements such as demand volume in order management, product quality in manufacturing processes, capacity usage in production management, traffic costs in transportation management, and so on. This paper presents a computerized system for implementing the forecasting activities required in SCM. For building a generic forecasting model applicable to SCM, a linear causal forecasting model is proposed and its coefficients are efficiently determined using the proposed genetic algorithms (GA), canonical GA and guided GA (GGA). Compared to canonical GA, GGA adopts a fitness function with penalty operators and uses population diversity index (PDI) to overcome premature convergence of the algorithm. The results obtained from two case studies show that the proposed GGA provides the best forecasting accuracy and greatly outperforms the regression analysis and canonical GA methods. A computerized system was developed to implement the forecasting functions and is successfully running in real glass manufacturing lines.     

连锁零售供应链多级库存协同决策研究

针对连锁零售供应链多级库存资源的动态优化配置问题,提出了在上层对库存策略和下层对物流分配方案协同寻优的多级库存双层规划模型。借鉴细粒度模型遗传算法的遗传操作具有局部性的特点,模拟微观群体交互作用的局部性,基于细粒度模型遗传算法的Agent群体行为优化算法和基于复杂适应系统涌现机理的协同决策机制,进行连锁零售供应链多级库存协同决策研究。通过算例实验对模型的有效性进行了验证。仿真实验结果表明,通过连锁零售供应链微观个体Agent的群体行为优化,从系统工程的角度,实现了连锁零售供应链多级库存的动态资源优化配置和信息共享,降低了多级库存管理与运营的总成本。     

一种劝说式多Agent供应链协商模型研究

好的协商模型对提高供应链协商效率有着重要的意义。提出了一种基于劝说式的多Agent供应链协商模型。对供应链协商模型框架和协商Agent的状态信息进行了形式化的定义,阐述了协商中的劝说方法、让步原则和提议交互过程。实践表明利用该模型建立起供应链协商支持系统能提高供应链伙伴协商效率和协商成功率。     

Coordination-based inventory management for deteriorating items in a two-echelon supply chain with profit sharing

This study develops a model for inventory management consisting of a two-echelon supply chain (SC) with profit sharing and deteriorating items. The retailer and the supplier act as the leader and follower, in which the supplier faces a huge setup cost and economic order quantity ordering strategy. The market demand is affected by the sale price of the product, and the inventory has a deterioration rate following a Weibull distribution. The retailer executes three profit-sharing mechanisms to motivate the supplier to participate in SC optimisation and to extend the life cycle of the product. A search algorithm is developed to determine the solutions as using the profit-sharing mechanisms. The outcomes from numerical experiments demonstrate the profitability of the proposed model.     

A decision rule for coordination of inventory and transportation in a two-stage supply chain with alternative supply sources

This paper deals with a two-stage supply chain that consists of two distribution centers and two retailers. Each member of the supply chain uses a (Q,R) inventory policy, and incurs standard inventory holding and backlog costs, as well as ordering and transportation costs. The distribution centers replenish their inventory from an outside supplier, and the retailers replenish inventory from one of the two distribution centers. When a retailer is ready to replenish its inventory that retailer must decide whether it should replenish from the first or second distribution center. We develop a decision rule that minimizes the total expected cost associated with all outstanding orders at the time of order placement; the retailers then repeatedly use this decision rule as a heuristic. A simulation study which compares the proposed policy to three traditional ordering policies illustrates how the proposed policy performs under different conditions. The numerical analysis shows that, over a large set of scenarios, the proposed policy outperforms the other three policies on average.     

A customer-centric IoT-based novel closed-loop supply chain model for WEEE management

Waste electrical and electronic equipment (WEEE) has been one of the widest and soaring solid wastes worldwide. Circular economy, as a sustainable paradigm, promotes closing the loop of e-products to prolong the life of WEEE. Hence, a sustainable Internet of things (IoT)-based closed-loop supply chain (CLSC) system is established considering the economic, environment and social dimensions. Due to the reality constraints, a simulation model with two scenarios is constructed to consider the customers’ behavior in the system. The attribute importance of customers’ behavior is analysed. Second-hand price and buy back price are shown to be two highly important factors, followed by peer pressure and social influence. Additionally, we present a sustainability assessment with the extant system using life cycle assessment, showing that our proposed system is more sustainable. Appropriate WEEE management using the proposed IoT-enabled system makes more profit and can reduce more greenhouse gas emissions and heavy metal contamination. In addition, with applying the proposed system, the number of people being protected from diseases caused by heavy metals can be significantly reduced.     

Optimal inventory control policy and supply chain coordination problem with carbon footprint constraints

Carbon footprint constraints exert pressure on supply chains to reexamine decisions. In this paper, we consider carbon transfer cost and carbon holding cost in a supply chain. A multiperiod dynamic programming model with carbon footprint constraints is presented to investigate the impact of carbon transfer cost and carbon holding cost on inventory control policy as well as the supply chain coordination problem. A two‐control limit inventory control policy is proved to be optimal and a contract with wholesale price, subsidy, and fixed setup cost is verified analytically to coordinate the supply chain. Finally, a numerical study is conducted to reveal managerial insights. We find that when the supply chain is coordinated, the chain's profit is more sensitive to carbon transfer cost while inventory level is more sensitive to carbon holding cost. Additionally, because of the complexity of the coordinated contract, when it is not easy to coordinate the supply chain, it is better to keep the values of wholesale price, subsidy, and fixed setup cost below the corresponding values for the coordinated supply chain.     

供应链中控制多级存储的射频辨识Push/Pull混合策略设计与仿真

由于射频辨识(radio frequency identification,RFID)激励的电子看板系统能够从远端看见供应链节点企业库存的状况,使得广域分布的供应链多级存储能够实现RFID激励的Pull控制.本文根据供应链分销网络多级存储的结构特点,以及系统运作期间各阶段节点企业的功能,在不同阶段采用不同的控制策略.因此,设计了多种不同的RFID激励的Push/Pull混合控制策略.为了比较和验证各混合策略对多级存储的控制性能,建立了以总库存成本、总缺货损失、总运行成本和库存周转率作为评价策略性能的指标体系.由于供应链系统的动态性与随机性,难以进行数学建模和精确求解,因此基于离散事件系统仿真原理,设计并实现了仿真模型.通过对各策略下多种结构的供应链分销网络多级存储的仿真,验证并分析了制造商阶段采用Push控制,分销商和零售商阶段采用Pull控制的策略的有效性和最优性.     

精敏供应链Stackelberg博弈EOQ决策模型

在非合作和合作两种不同情景下,不考虑缺货损失条件,研究一个主导方供应商和两个跟从方制造商不同订货成本结构的两层精敏供应链上游段Stackelberg博弈的EOQ决策模型。引入供应商价格折扣策略,通过模型分析与求解,得出Stackelberg博弈下的EOQ决策均衡点,改善了精敏供应链上游段的整体运行效率,提高了供应链参与成员的各自收益。通过实例分析,验证了模型的可行性。     

Efficient multi-objective optimization of supply chain with returned products

Closed loop supply chain aims at integrating return products in the traditional supply chain processes. The return flows generate new uncertain elements (returns and leadtimes) and optimization of inventory control in this context is a complex issue. Inventory policies have to generate good performances (service level, cost) and be easy to implement in practice. A supply chain model based on simulation and multi-objective optimization is proposed to optimize control policies for multi-echelon supply chain with returned products. The method is tested on three inventory policies which correspond to different ways of making decision.     

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.

     

供应商管理库存中的一种供需问题及优化模型

在供应商管理库存(VMI)的条件下,当供应商为不同区域的零售商供应同种商品时,为了降低供应商的供应成本,根据各零售商未来T期的需求,建立了以总成本最小为目标的供应商协调供应模型,并分别用启发式算法和遗传算法求解该模型。通过算例表明,相对于单纯以按时按量满足各零售商的需求为目标的供应方案,这两种方法得到的方案总成本均大大降低,而且遗传算法的解要优于启发式算法的解。