考虑偏好与合作的供应链网络设计与优化

提出了考虑核心企业决策偏好与成员企业合作意愿的双目标供应链网络设计与优化问题。应用模糊多目标规划方法,将决策者对各个目标的不精确期望水平考虑到供应链网络的设计与优化模型中。研究了集中决策模式下核心决策者的不同目标偏好与分散决策模式下各组织成员群体决策的合作意愿,对供应链的各个目标及网络优化配置的影响。结果表明,“极大极小”算子体现了核心决策者对各个目标的偏好,但大权重目标以牺牲小权重目标的值为代价的。新的“模糊与”补偿算子能使供应链的各个目标值获得理想的均衡效果,体现了供应网络中核心企业与其他成员企业群体协商决策的管理思想与行为特征。     

面向Agent的集群式供应链服务系统设计方法研究

为了帮助中小型企业(SMEs)应对经济全球化的挑战,“集群式供应链”的概念作为一种新型管理模式被提了出来,它集成了工业集群和供应链两个方面的优势.目前,对集群供应链的研究仍然处于初级阶段,其理论结果难以应用到实践当中.基于此背景,提出一个集群式供应链服务系统的设计方法,以Agent模型与Web服务之间的模型映射为桥梁,整合来自不同学科领域的研究成果,从而弥补该领域理论和实践之间的鸿沟.最后,通过浙江织里镇的童装工业集群的案例,来解释如何使用该方法指导集群式供应链的构建和开发,主要包括三个阶段:商业建模、模型映射和实现建模.     

考虑产品替代的供应链协调问题研究

替代品大大增加了企业间的竞争,使企业难以达到所期望的盈利水平。对供应链进行合理有效的管理可最大限度地促进企业适应当今多变的市场环境。人们对于产品的需求不仅仅取决于产品本身的价格,也取决于互补产品的价格。对此,构建一个以产品替代的供应链协调问题为研究目标,以两种供应链管理模式(集中供应链(CSC)和分散供应链(DSC))为依托,通过建立混合整数规划模型并对相关参数进行验证,得出集中供应链模式更能灵活应对当今市场。     

The impact of service system on the implementation of cluster supply chain

As a new management pattern, ??cluster supply chain?? (CSC) can help small and medium enterprises (SMEs) in China to face the sharp global competitions through all kinds of collaboration. However, a major challenge in implementing CSC is the gap between the related theories and practices in the field. In order to bridge the gap, this paper presents the JingCheng Mechanical & Electrical Holding co., Ltd. (JCH) as a case study to explain the key problems in the practice of cluster supply chain: What are the specific conditions for the implementation of cluster supply chain? What are the advantages and challenges of implementing cluster supply chain? Furthermore, the role of service supporting system is emphasized, which has driven a process of transforming CSC theories into practices. Through the case study of JCH, we clarify the role of service system in the actual construction and operation of cluster supply chain, which can promote the rapid adoption of CSC and show successful results as it should be.     

基于二层规划的供应链定价决策研究

针对一个单一制造商与多个零售商构成的分布控制型供应链,其中制造商作为主导者确定批发价,零售商确定各自的零售价,市场需求量由零售价格决定的问题,利用二层规划模型研究了具有S tacke lberg博弈特征的定价决策,并给出了混沌搜索求解算法,同时给出供应链成员合作的条件.研究结论表明,分布控制型供应链虽然不能保证系统最优,但却能实现成员利益最大化,因而均衡状态下的价格是稳定的.最后通过实例验证了给出的结论.     

电–气互联系统的气电解耦分布式多目标优化调度

本文基于能源互联网背景建立了一种计及供能成本、碳排放量和净负荷曲线平滑度的电–气互联系统多目标优化模型,并采用线性化方法将非线性优化模型转化为混合整数线性规划模型.同时,为了求解该模型,实现各能源的协同互补利用,提高能源的利用率,本文在保障各能源网络分散自治权的基础上提出一种基于气电解耦的分布式多目标优化算法,以气电解耦优化的方式实现电、气系统的分散自治.所提算法将原系统的多目标优化问题分解为电网和气网的子优化问题,并采用独立的优化器完成子问题的求解.电网和气网仅需交换少量边界变量以及虚拟目标因子分别进行全局调整即可获得多目标解.最后,本文根据修改的IEEE 39节点电力网络和比利时20节点天然气网络搭建模型并进行仿真分析,结果验证:所提算法能够完成电–气互联系统的气电解耦并实现多目标并行求解,从而提高系统信息私密性、实现各能源网络的分散自治.     

Cost allocation model for optimizing supply chain inventory with controllable lead time

The coordination issue of a decentralized supply chain composed of a vendor and a buyer is considered in this paper. The vendor offers a single product to the buyer and the lead time can be controllable with adding crashing cost. Two supply chain inventory models with controllable lead time under different decision modes are considered, one is proposed under decentralized model based on Stackelberg model, the other is proposed under centralized model of the integrated supply chain. The solution procedures are also suggested to get the optimal solutions of these two models. In addition, an asymmetric Nash bargaining model based on satisfaction level is also developed to get the best cost allocation ratio between the vendor and the buyer by taking their individual rationalities into consideration. The results of numerical example show that shortening lead time reasonably can reduce inventory cost and the cost allocation model based on satisfaction level developed in this paper is effective.     

Decentralized and centralized model predictive control to reduce the bullwhip effect in supply chain management

Mitigating the bullwhip effect is one of crucial problems in supply chain management. In this research, centralized and decentralized model predictive control strategies are applied to control inventory positions and to reduce the bullwhip effect in a benchmark four-echelon supply chain. The supply chain under consideration is described by discrete dynamic models characterized by balance equations on product and information flows with an ordering policy serving as the control schemes. In the decentralized control strategy, a MPC-EPSAC (Extended Prediction Self-Adaptive Control) approach is used to predict the changes in the inventory position levels. A closed-form solution of an optimal ordering decision for each echelon is obtained by locally minimizing a cost function, which consists of the errors between predicted inventory position levels and their setpoints, and a weighting function that penalizes orders. The single model predictive controller used in centralized control strategy optimizes globally and finds an optimal ordering policy for each echelon. The controller relies on a linear discrete-time state-space model to predict system outputs. But the predictions are approached by either of two multi-step predictors depending on whether the states of the controller model are directly observed or not. The objective function takes a quadratic form and thus the resulting optimization problem can be solved via standard quadratic programming method. The comparisons on performances of the two MPC strategies are illustrated with a numerical example.     

Decision optimization analysis on supply chain resource integration in fourth party logistics

In recent years, the successful operation of the fourth party logistics (4PL) in practice has gradually demonstrated that it is an effective mode to integrate the complicated resources of a supply chain reasonably, efficiently and flexibly. However, there are no effective quantitative methods to guide the resource integration practices of enterprises and this situation will inevitably limit the practical application of 4PL and will become a major bottleneck of showing its superiorities. To solve this operational bottleneck in 4PL, this paper analyzes thoroughly the characteristics of the supply chain resource integration in 4PL mode from a quantitative view, set up an operational framework by case studies of surveyed enterprises combined with the empirical analyses of the supply chain resource integration. On this basis, this paper puts forward a decision optimization method of supply chain resource integration in 4PL based on the discovery, analyses and judgment about the dominant factors in the integration operations, then, sets up a mathematics optimization model for integration decision and an improved ant colony optimization (ACO) algorithm to solve the decision problem. Finally, the paper uses a case simulation to illustrate that the optimization method and algorithm are feasible and valid.     

基于WTP差异化的再制造闭环供应链利益协调机制

考虑到消费者对新产品和再制造产品支付意愿的差异, 分别建立了分散决策和集中决策下多周期再制造闭环供应链的决策模型, 得出了各供应链成员的最优决策, 通过shapley值法来确定利益协调机制, 并利用数值仿真对模型进行求解和分析。研究结果表明, 分散决策存在效益缺失, 中间商的减少可有效提高供应链系统的效益; 可通过shapley值对再制造闭环供应链的利益进行合理有效的分配。     

Formulation and analysis of dynamic supply chain of backfill in construction waste management using agent-based modeling

Backfill is the excavated material from earthworks, which constitutes over 50% of the construction wastes in Hong Kong. This paper considers a supply chain that consists of construction sites, landfills and commercial sources in which operators seek cooperation to maximize backfill reuse and improve waste recovery efficiency. Unlike the ordinary material supply chain in manufacturing industries, the supply chain for backfill involves many dynamic processes, which increases the complexity of analyzing and solving the logistic issue. Therefore, this study attempts to identify an appropriate methodology to analyze the dynamic supply chain, for facilitating the backfill reuse. A centralized optimization model and a distributed agent-based model are proposed and implemented in comparing their performances. The centralized optimization model can obtain a global optimum but requires sharing of complete information from all supply chain entities, resulting in barriers for implementation. In addition, whenever the backfill supply chain changes, the centralized optimization model needs to reconfigure the network structure and recompute the optimum. The distributed agent-based model focuses on task distribution and cooperation between business entities in the backfill supply chain. In the agent-based model, decision making and communication between construction sites, landfills, and commercial sources are emulated by a number of autonomous agents. They perform together through a negotiation algorithm for optimizing the supply chain configuration that reduces the backfill shipment cost. A comparative study indicates that the agent-based model is more capable of studying the dynamic backfill supply chain due to its decentralization of optimization and fast reaction to unexpected disturbances.     

电商平台主导下的供应链推广策略研究

结合电商平台快速发展的时代背景,构建了电商平台主导、制造商跟随的两级电商供应链博弈模型,分别研究了集中决策与分散决策下的产品定价、服务水平和推广水平,分析了佣金率对最优决策和供应链成员利润的影响,并设计了"推广成本分摊"策略.结果表明:当佣金率较低时,集中决策下的产品定价和服务水平、推广水平高于分散决策下的最优决策;当...     

供应链动态合作广告策略

研究产品信誉受广告投入水平影响的供应链合作广告问题,建立具有广告投入水平抑制作用的产品信誉动态模型.通过哈密顿-雅可比-贝尔曼方程分别得到制造商和零售商在分散决策和集中决策下的最优广告策略以及在分散决策下制造商的最优合作广告参与率,比较发现,集中决策下制造商和零售商的最优广告投入水平高于分散决策下的相应值.设计了双边补贴策略来协调供应链.数值仿真实验验证了所得结论的正确性.     

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。     

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.     

石化企业内部供应链业务流程分析及建模仿真

石化企业是典型的流程型企业,是石化供应链的核心企业,其内部业务流程管理对整个石化供应链运作性能具有决定性作用。以某石化公司为研究对象,分析其内部供应链原有业务流程,建立相应的概念模型;为了优化原有企业内部供应链业务流程,引入SCOR建模框架;采用AnyLogic仿真平台,分别建立采用SCOR框架前后企业内部供应链的仿真模型。仿真分析表明,采用SCOR框架改进业务流程,可以有效改善企业内部供应链性能。     

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。     

Simulation-based optimization of process control policies for inventory management in supply chains

A simulation-based optimization framework involving simultaneous perturbation stochastic approximation (SPSA) is presented as a means for optimally specifying parameters of internal model control (IMC) and model predictive control (MPC)-based decision policies for inventory management in supply chains under conditions involving supply and demand uncertainty. The effective use of the SPSA technique serves to enhance the performance and functionality of this class of decision algorithms and is illustrated with case studies involving the simultaneous optimization of controller tuning parameters and safety stock levels for supply chain networks inspired from semiconductor manufacturing. The results of the case studies demonstrate that safety stock levels can be significantly reduced and financial benefits achieved while maintaining satisfactory operating performance in the supply chain.     

再制造率随机的闭环供应链产品差别定价策略

考虑闭环供应链的差别定价问题, 制造商回收废旧产品, 并生产新产品和再制造产品, 再制造率随机. 采用Stackelberg 博弈方法, 研究集中决策和分散决策下相应产品的最优定价, 给出供应链各成员的最优利润. 结果表明:若制造商对产品延迟定价, 则集中决策下回收价格高于分散决策, 而销售价格均低于分散决策; 当零售商的保守利润不低于一定值时, 集中决策下总利润不低于分散决策, 制造商可以采用改进的两部定价契约协调供应链.

     

带有订单转保理的供应链金融的收益共享博弈模型

当作为供应商的中小企业出现了严重的财务困境问题时,急需有效融资工具和创新管理模式加以解决.订单转保理可以令资质良好的零售商为资金短缺的供应商提供融资担保,有效解决供应商的订单减少和融资难的问题.然而,分散决策的订单转保理融资模式,使得做担保的零售商的收益降低,不能明显改善供应链效率.针对此问题,研究订单转保理模式下的供应链协调模型,并重点研究由供应商与零售商组成的二级供应链的订单转保理收益共享模型.研究发现:收益共享决策模型供应链总收益小于集中决策供应链总收益,大于分散决策的供应链总收益,表明供应链成员相互合作程度越高,越有利于供应链发展,从而表明协调在供应链中发挥重要作用.然而,集中决策模型只能得到供应链最优总收益,无法得到供应商和零售商的最优收益.收益共享模型不仅能够提高产品订货量,降低产品批发价格,增加供应商和零售商的收益,而且通过最优的收益共享系数可以得到供应商和零售商的最优收益.收益共享机制能够为供应商和零售商共赢协调发展提供新的运作管理模式.