Inventory replenishment and delivery planning in a two-level supply chain with compound Poisson demands

This paper presents a model for integrating inventory replenishment and delivery planning in a two-level supply chain consisting of a supplier and a retailer. The supplier is authorized to manage the inventory level of the retailer by using the information on demands from final customers and the inventory level of the retailer. The problem considered here is to determine order-up-to levels of the supplier and the retailer simultaneously for the objective of minimizing the expected long-run average cost, which is composed of replenishment cost at the supplier, delivery cost to the retailer, and inventory holding costs at both members. We develop a renewal theoretic optimization model for a case of compound Poisson demands with distribution-free order quantities and present an approximation method for obtaining a solution of the problem. In addition, a closed-form solution is derived for the problem with a special case of compound Poisson demands, in which demand quantities follow an exponential distribution. A series of simulation tests show that the solutions obtained from the approximated cost functions are reasonably good.     

A constrained Nash bargaining approach to the stock rationing problem in multi-echelon supply chains

In order to survive in the global volatile market place, supply chain analysts are brainstorming to arrive at robust inventory control policies that prevents inventory worth of millions of dollars to get tied up in the chain and at the same time ensures to achieve the differentiated customer service levels. Inventory rationing is a useful strategy to tackle the above problem of conflicting objectives, i.e., minimizing inventory costs (holding costs and backorder costs) and achieving the desired customer service levels. In this paper, we consider a multi-echelon supply distribution system and pose the stock allocation problem in a constrained Nash bargaining (NB) setting. The objective of the model is to determine a set of rationing fractions at the central depot in order to minimize the order-up-to level inventory yet exactly achieving the differentiated target fill rates. It is our firm belief that the distribution resource planning (DRP) managers will find the proposed models a useful tool in their stock allocation decision-making process. Rigorous computational experiments suggests that our approach performs better than the existing ones for this important problem.     

Impact of forecasting methods on variance ratio in order-up-to level policy

This paper considers the impact of forecasting methods on the bullwhip effect for a simple replenishment system in which a first-order autoregressive process describes the customer demand and an order-up-to inventory policy characterizes the replenishment decision. The impact of exponential smoothing and minimum mean squared error forecasting is measured for both the bullwhip effect and inventory variances. Previous similar studies have focused on investigating the impact of forecasting methods on bullwhip effect. However, little research has been carried out to explore the impact of forecasting methods for both bullwhip effect and inventory variances. Through simulation experiments, it has been found that depending on the structure of the demand process, the appropriate selection of forecasting technique can reduce, or even eliminate (i.e., “dewhip”) the bullwhip effect. However, in terms of inventory variances it has been shown that the inventory variances for the exponential smoothing are greater than the minimum mean squared error forecasting method and that gap increases as lead time increases. These findings will help companies to choose the appropriate forecasting technique depending on the nature of demand. These guidelines can help companies to reduce the bullwhip effect and inventory variances across supply chain.     

A heuristic technique for inventory replenishment policy with increasing demand pattern and shortage allowance

In the growth stage of a product life cycle, the demand rate is usually unstable and follows an increasing pattern. The traditional inventory policies, which have been developed for stationary demand pattern, are not appropriate to this situation. Although there exist some researches in the past dealing with inventory policy for the case of increasing demand pattern, most of them focused on the inventory systems in which shortages are not allowed. In reality, the presence of shortages is sometimes economically preferable when holding cost is significant as compared with shortage cost. The aim of the research presented in this paper is, therefore, to develop a replenishment policy for inventory systems with nonlinear increasing demand pattern and shortage allowance in such a way that the total demand during a predefined planning horizon can be exactly met. A heuristic technique to help determine the operational parameters for the inventory policy is then developed. In the proposed heuristic technique, the consecutive improvement method developed by Wang (Comput Oper Res, 29:1819–1825, 2002) will first be used to help determine replenishment times. And then, a new concept of reduction cost, which is defined as the difference between the holding cost when shortage is allowed and the incurred shortage cost, is introduced and applied to help find the optimal shortage starting point in each replenishment cycle. Numerical experiments are also conducted to illustrate the applicability of the proposed technique.     

A replenishment policy based on joint optimization in a downstream pharmaceutical supply chain: centralized vs. decentralized replenishment

This paper considers a number of problems in a pharmaceutical downstream supply chain under specific constraints related to pharmaceutical products (e.g., their expiry date and regulations) and to inventory control (e.g., low prices of products, gift products or prices near zero, shortages prohibited but excess inventory allowed). As traditional models of inventory control and replenishment cannot optimize the total cost of the system, it is very important to consider the transportation cost as well. In this paper, we take into account some of these constraints and propose two models for multi-product replenishment policies, namely centralized and decentralized models. We seek to identify the best quantity and period of replenishment of products for a joint optimization of inventory and transportation costs. The proposed models can be applied to a specific family of products with a stable demand and high turnover rate, low prices (or gift products for some of them), and without any shortage. These two models are compared and the global approach is illustrated by a numerical example taken from a real-case study.     

一类供应链系统在最大库存策略下的性能分析

为了增强企业的柔性、可靠性和响应性,根据环境变化实时做出决策,构建了一类链式供应链系统的动态模型。针对由一个制造商、一个分销商和一个零售商组成的供应链系统,建立了带有成员库存能力约束的离散时间状态空间模型,该模型可扩展为一般链式供应链系统。以客户满意度和平均周期费用为指标,通过仿真分析了最大库存策略下系统的性能特点,指出此时系统的动态性差,策略不够灵活。根据反馈控制理论提出了改进的最大库存策略,该策略可根据性能要求和需求模式改变控制参数。仿真分析表明,改进的最大库存策略的控制效果明显优于原策略。     

Impact of information sharing on supply chain performance

In this study, the effect of information sharing on on-time delivery rate and total cost in a supply chain is investigated via simulation. The experimental factors include capacity tightness, resource reliability, and information sharing modes, which are sharing of resource reliability information, customer demand, and inventory level. The simulation results show that all three experimental factors are statistically significant. Yet, the information sharing modes perform uniquely when the main and interaction effects are analyzed. This study demonstrates that the level of interaction between capacity tightness, resource reliability, and information sharing modes depend on the operational parameters, as well as the flexibility available in a supply chain. Therefore, it may be more feasible to introduce additional flexibility instead of solely focusing on information sharing capability as a coordination tool.     

信息共享环境下多级复杂供需链系统的库存成本分析

以一个制造商、多个互异的分销商和多个互异的零售商组成的复杂供需链系统为研究对象,建立了供需链系统库存成本模型,对各个企业的信息共享价值进行了分析计算.结果表明,制造商和分销商均能够从共享零售商的需求信息中获利,而零售商则从信息共享中得不到任何利益,因此需要制订一定的利益分配机制,以促进供需链信息共享的实现.     

闭环物流宏微观协同决策模型

在原有的正向物流基础上,将逆向物流并入其中,构成一个闭环的物流网络。以总闭环物流运输成本、库存成本、惩罚成本和建设成本之和最低为目标,建立闭环物流网络数学规划模型,实现了在闭环物流系统宏观总需求前提下的微观物流计划安排,并利用分支定界法解出其最优解。实例分析结果表明,宏微观协同决策模型较好地补充了传统闭环物流模型的静态单目标单产品问题,可以解决动态多目标多产品的决策问题,实现了供应链设计宏观战略和微观战术的结合。     

基于CPFR的供应链体系结构和运作研究

合作计划、预测与补给是近年来出现的一种面向供应链的新型合作伙伴关系策略 ,对于供应链伙伴改善合作关系、提高预测准确度和供应链效率、减少库存、提高消费者满意程度等均有重要的意义。本文阐述了合作计划、预测与补给的概念和特点 ,提出了基于合作计划、预测与补给的供应链体系结构和合作关系 ,分析和论述了其运作过程 ,建立了合作企业价值观     

Maintaining the balance [replenishment and inventory]

Demand and replenishment are critically dependent on how effectively information systems are used and how well demand signals, batching rules and effective forecasting, are managed and converted into plans and procurement actions. The supply and inventory relationship are more concerned with what is actually made, where inventory is placed and how it is moved through the supply chain. A better understanding of the issues and strategies can be achieved by examining the many combinations of supply and demand and consider them as different scenarios. In this paper three scenarios are cited.     

Capacities-based supply chain network design considering demand uncertainty using two-stage stochastic programming

The design of a supply chain (SC) aims to minimize cost so the product can reach the customer at the cheapest cost with flexible demand. The demand of a product is variable with time and environment. Most of the researchers have considered investment cost, processing cost, and transportation cost as variable costs to minimize the cost while considering a constant demand. In actual practice, the demands are flexible. In this paper, a two-stage stochastic programming model has been proposed for a capacities-based network design of a supply chain for flexible demands while considering inventory carrying cost and missed opportunity cost in addition to the above-mentioned costs. It will enhance the logistic planning and seek the location network optimally. Furthermore, in the first stage, decision variables represent different nodes (facility locations of echelons) of the supply chain, with the assumption that they will be considered at the design stage before uncertain parameters are unveiled. On the other hand, decision variables related to the amount of products to be produced and stored in the nodes of the SC, the flows of materials among the entities of the network, and shortfalls and excess at the customer centers are considered as second-stage variables. The methodology has been illustrated by solving an example. It was found that the proposed model yields more feasible and advantageous results.     

供需链中的结盟企业库存管理

供需链中核心企业与结盟企业在风险分担和库存信息上存在不对称，在提货时存在“局部利益最大化”问题，核心企业仅能通过提货量控制结盟企业库存。结加存管理包括根据外部事件及反馈信息进行结盟企业库存维护和利用提货量来控制结盟企业库存，本文建立了结盟企业库存维护的形式化模型和库存控制的随机模型，并提出了一种层次型混合算法。     

通货膨胀环境下需求依赖库存的经济订货批量模型

为考虑通货膨胀和货币时间价值对库存的影响,研究了通货膨胀的条件下需求受库存水平影响且允许短缺发生的经济订货批量问题,其中通货膨胀率由内部通货膨胀率与外部通货膨胀率两部分组成。以系统成本最小化为目标,建立了四个不同补货策略下的仿真模型,并提供了寻求模型整体最优解的简单方法。最后,通过实例对这四个模型进行了比较,同时分析了参数变化对模型最优解的影响。     

Adaptive inventory control models for supply chain management

Uncertainties inherent in customer demands make it difficult for supply chains to achieve just-in-time inventory replenishment, resulting in loosing sales opportunities or keeping excessive chain-wide inventories. In this paper, we propose two adaptive inventory-control models for a supply chain consisting of one supplier and multiple retailers. The one is a centralized model and the other is a decentralized model. The objective of the two models is to satisfy a target service level predefined for each retailer. The inventory-control parameters of the supplier and retailers are safety lead time and safety stocks, respectively. Unlike most extant inventory-control approaches, modelling the uncertainty of customer demand as a statistical distribution is not a prerequisite in the two models. Instead, using a reinforcement learning technique called action-value method, the control parameters are designed to adaptively change as customer-demand patterns changes. A simulation-based experiment was performed to compare the performance of the two inventory-control models.     

基于ASP平台的供应链协同运作模式研究

激烈的市场竞争环境给供应链管理模式下的制造企业提出了新的发展要求,供应链协同是改进消费者服务,减少库存,减少供应链成本,提升竞争力,提高消费者忠诚度的一条途径.为了实现供应链协同运作的目的,需要在跨平台、跨应用方面达成协同并实现协同管理.通过研究开发网络化制造环境下供应链协同的企业动态联盟运作模式,建立基于应用服务供应商(ASP)的供应链协同运作平台,实现集成企业中采购、库存生产计划等业务过程的管理协同和信息协同,增强对市场需求不确定性的快速反应能力,提高供应链的整体竞争力.     

RFID技术在彩电行业供应链中的应用

针对彩电行业发展现状和RFID系统的工作特点,分析了RFID技术应用于彩电供应链管理的优势,详细描述了基于RFID技术在彩电原材料供应、生产制造、库存管理、运输、分拣、流通销售、售后服务及报废回收等节点的应用,实现了彩电供应链整体流程的信息共享,并就RFID实施中的关键技术进行了阐述。     

Decentralised production-distribution planning system using collaborative agents in supply chain network

With the fast development of information technology and the global market, collaboration between different functional units in a supply chain becomes one of the most critical factors for global companies to respond to rapid changes in customer needs and increase the efficiency of the whole supply chain. This supply chain environment requires a production-distribution planning system to enable the collaboration between production and distribution units more quickly and orderly. Generally, collaboration in a supply chain needs to resolve conflicts between two decentralised functional units, because each unit tries to locally minimise its own costs, not the overall supply chain costs. Also, there exists incomplete information sharing according to the information privacy of each functional unit. This paper proposes a decentralised production-distribution planning system using collaborative agents that can efficiently mediate the planning gaps between two decentralised planning functions: production and distribution. The validity of collaborative-agent model has been shown using some lemmas and numerical examples.     

面向供需链协同的信息共享价值分配机制

为实现供需链协同,合理设计信息共享价值分配机制,针对由一个制造商、多个同质分销商、多个同质零售商所组成的三级供需链系统,从库存持有水平的角度定量分析各成员的信息共享价值.在此基础上,应用多人合作博弈理论,建立了供需链库存效益分配模型,并采用τ值法求解该模型,给出了满意、协调、协同等多种分配方案.数值实验结果表明,基于τ值法的协同分配方案能够促使供需链协同的实现.     

双渠道多期供应链网络均衡模型研究

为适应信息化和高度动态化的发展,研究了在实体和网上两种交易渠道下,由制造市场、零售市场和需求市场组成的三层动态供应链网络的均衡问题,在静态供应链网络均衡模型的基础上,考虑了库存和网上交易对供应链网络的影响.分别对制造市场、零售市场和需求市场的决策者的独立决策行为及其相互作用进行了分析,构建了各层市场的有限维变分不等式,并将变分不等式问题转化为等价的互补问题的形式,给出了经济解释,得到了最终的双渠道多期供应链网络均衡模型,并给出了箅例分析.求解得到的均衡产量、交易量、库存量和均衡价格对供应链上企业的经营具有指导意义.