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。     

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.     

船舶主机企业刀工具库存补充技术的研究

分析了船舶主机企业刀工具库存管理的特点,提出了采用自适应系数的二次指数平均法及标准正态分布函数建立的企业刀工具库存补充模型,并通过具体的实例分析了其有效性.     

Inventory systems with random arrival of shipments

In single-period inventory models, neither excess demand nor excess inventory can be carried forward to the next period. In stochastic multi-period models, an order is placed at some point in time during the cycle, and lead-time is considered to be either constant or random. Lead-time demand, however, is assumed to be probabilistic. At the time an order is placed, the amount of inventory which will be on hand when replenishment arrives is unknown. In this paper, we propose a variation of these models to determine the optimal economic order quantity. Shipments arrive according to a Poisson process. The status of the inventory becomes known at the time of the arrival of the shipment, and the selection of order quantity is made at that time. However, the arrival time of future shipments is uncertain. It is also demonstrated that traditional single- and multi-period inventory models can be obtained as special cases of the proposed model.     

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 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.     

Optimal pricing and replenishment policies of an EOQ model for non-instantaneous deteriorating items with shortages

This paper discusses the optimal pricing and replenishment policies of an economic order quantity model for non-instantaneous deteriorating items with partial backlogging over an infinite time horizon. The model is studied under the replenishment policy starting with no shortages. The backlogging rate is any non-increasing function of the waiting time up to the next replenishment. The objective of this model is to maximize the total profit which includes the sales revenue, purchasing cost, set up cost, holding cost, shortage cost, and opportunity cost due to lost sales. Here, the selling price, replenishment quantity, replenishment cycle length, and the time duration of the positive inventory level are taken as decision variables to maximize the profit of the inventory system. The existence and the uniqueness of the solution of the proposed inventory system are examined. We suggest a solution procedure to find the optimal solution of the described model. Numerical examples are presented to determine the developed model and the solution procedure. Sensitivity analysis of the optimal solution with respect to major parameters is carried out and some useful managerial results are obtained.     

一种基于动态批量的非平稳需求库存管理方法

非平稳需求的库存管理问题是运作管理的一个难题,对此提出了一个订购提前期可以任意固定的非平稳需求库存管理模型.在一定长度的计划期上,每个时间段上的动态订购点和订购批量可以通过求解该模型确定.考虑到需求的非平稳特征,采用滚动计划的方法,并设定计划将其冻结为1,以更好地跟踪需求的变化;然后通过计划的滚动,实现需求分布的更新和计划期上各时间段订购点与订购批量的更新.实证分析结果证明了所提出模型与方法的可行性与优越性.     

Optimal replenishment policies for deteriorating control wafers inventory

This paper considers a control wafers replenishment problem with inventory deterioration. In the process, control wafers begin to deteriorate after the pre-disposition. The objective of this research is to minimize the total cost of control wafers, where the cost includes ordering cost, holding cost and purchase cost. We first formulate the control wafers inventory problem as a dynamic programming model. We then transform the control wafers’ inventory problem into the mixed 0–1 linear programming model. An illustrative example with four cases is used to illustrate the practicality of these models, and sensitivity analysis is applied to understand the impact of parameters to these models. The results demonstrate that the proposed mixed 0–1 linear programming model is an effective tool for determining the replenishment of control wafers for multi-periods.     

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.     

联合生产存储问题的模拟退火算法

对确定性需求的联合补充生产存储控制系统进行分析，得出其关键问题是确定系统的联合生产补充周期和各产品的生产补充周期。建立了相应的模型，提出一个模拟退火算法，通过算例表明该算法可得出较优的可行解，与其他算法比较可以更有效地解决此类问题。     

Scheduling and replenishment plan for an integrated deteriorating inventory model with stock-dependent selling rate

An integrated approach is used to clarify the critical issues of scheduling and replenishment planning in an advanced inventory system under stock-dependent selling rate environment. This is because integration removes the barriers between enterprises and improves overall performance. A close collaboration such as just-in-time (JIT) operations also improves product quality of the supply chain. Different from the single-stage inventory model, this study develops an integrated two-stage production-inventory deteriorating model for the buyer and the supplier with stock-dependent selling rate, as well as considering imperfect items and JIT multiple deliveries. Our paper proposes a significant method using a time-weighted-inventory approach to analyze the supplier’s saw-tooth holding cost. We derive the optimal number of inspection, optimal deliveries and the optimal delivery-time interval. A numerical example is also presented to illustrate the theory. The results show that the fixed demand rate, the holding cost and the unit inspection cost are critical in the management of the deteriorating inventory model.     

Joint inventory and transshipment control for perishable products of a two-period lifetime

We analyze the impact of transshipments among retailers on their inventory replenishment decisions when products are perishable. Previous studies have shown that transshipments improve their operational efficiencies through inventory reallocation. However, these studies have not investigated transshipments for perishable products having a limited lifetime. In this paper, we consider a centrally managed firm owning several retail stores, which coordinates their replenishment policies along with the utilization of transshipments for perishable goods of a two-period lifetime. For this, the single-period planning horizon is analyzed, with a general solution approach for the optimal replenishment and transshipment decisions. We further present a designated solution approach for a two-location system as a special case and illustrate numerical examples in order to highlight the potential value of implementing transshipments for perishable products.     

Modeling and solving a one-supplier multi-vehicle production-inventory-distribution problem with clustered retailers

This paper considers a supply chain management problem which integrates production, inventory, and distribution decisions. The supply chain is composed of one supplier production facility and several retailers located in a given geographic region. The supplier is responsible for the production and the replenishment of the inventory of retailers, in a vendor managed inventory (VMI) context. The distance between retailers is negligible compared to the distance between the supplier and the retailers’ region. Thus, for each vehicle, there is a major fixed cost for traveling to the cluster of retailers and a minor fixed cost for visiting each individual retailer. The problem consists of determining quantities to be produced, quantities to be delivered to retailers, vehicles to be used, and retailers to be serviced by each vehicle. This problem is an extension of the one warehouse multi-retailer problem with the consideration of production planning and storage and vehicle capacity limitations in addition to fixed vehicle utilization costs and retailer servicing costs. The objective is to minimize a total cost composed of production, transportation, and inventory holding costs at the supplier and at the retailers. Two mixed integer linear programming formulations are proposed and six families of valid inequalities are added to strengthen these formulations. Two of these families are new and the others are adapted from the literature. The numerical results show that the valid inequalities considerably improve the quality of the formulations. Moreover, the parameters that influence the most computational times are analyzed.     

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.     

A Simulation Study of Dynamic Order-up-to Policies in a Supply Chain with Non-Stationary Customer Demand and Information Sharing

This study deals with the development of heuristic settings for dynamic order-up-to levels at different installations in a supply chain with non-stationary customer demand, in order to minimize the sum of inventory, shortage and transport costs. Balance equations are developed to capture the dynamics of supply chain. Mathematical expressions are derived to determine the dynamic order-up-to levels as a function of forecasted demand, forecasted replenishment leadtime and safety factor. Towards this attempt, different heuristic settings with respect to the safety factor are first proposed. Next, three levels of information sharing among the members of the supply chain are considered to study the impact of information sharing on the total cost. Finally, the use of a forecasting technique for predicting the replenishment leadtime is considered. A supply chain is simulated to evaluate the proposed dynamic order-up-to policies based on various heuristic settings. It is found that the use of forecast of replenishment leadtime and customer demand information sharing, and the proposed safety-stock heuristic settings in the determination of dynamic order-up-to levels, significantly reduce the sum of discounted inventory, shortage and transport costs of the supply chain.     

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。     

基于MRPⅡ的库存控制模型研究

结合数理统计的方法提出了一种基于MRPⅠ的库存控制模型,它既能运用MRPⅡ的主生产计划和物料清单文件来产生最终物料的数量和提前期,又能利用数理统计的方法来确定最合理的订购批量和订购时间。实践证明,本模型既能有效地降低库存资金的占用,又能提高库存管理水平,具有很强的现实指导意义。     

Algorithms for efficient planning and operation of a particular FMS

This article is a detailed case study of a particular FMS that will be operational in 1989. It describes the daily planning and operating problems that will need to be addressed. The algorithms that will operate this system are presented. Given the daily changing production requirements, the algorithms begin with an aggregate planning feasibility check. Then planning, scheduling, inventory management, and breakdowns are addressed.The key problems in operating this system are tool management problems. Detailed tooling data and their analysis are presented in an appendix to address these problems.