Vendor managed inventory with consignment stock for supply chain with stock- and price-dependent demand

This paper presents a single vendor–single buyer coordinated model. The vendor produces a single deteriorating item and transfers it to the buyer in equal shipments. The model is based on vendor managed inventory with consignment stock (VMI-CS) agreement in which the vendor uses the buyer’s warehouse. The buyer stocks items both on his shelf and in his warehouse. The demand is assumed to be linearly sensitive to inventory level and selling price. The objective is to determine variables that maximise the total profit. An exact solution procedure is proposed to find the optimal solution. Numerical results show that supply chain members will benefit from the advantages of economies of scale in coordinated model with VMI-CS policy.     

Information inaccuracy in inventory systems: stock loss and stockout

Many companies have automated their inventory management processes and now rely on information systems when making critical decisions. However, if the information is inaccurate, the ability of the system to provide a high availability of products at the minimal operating cost can be compromised. In this paper, analytical and simulation modelling demonstrate that even a small rate of stock loss undetected by the information system can lead to inventory inaccuracy that disrupts the replenishment process and creates severe out-of-stock situations. In fact, revenue losses due to out-of-stock situations can far outweigh the stock losses themselves. This sensitivity of the performance to the inventory inaccuracy becomes even greater in systems operating in lean environments. Motivated by an automatic product identification technology under development at the Auto-ID Center at MIT, various methods of compensating for the inventory inaccuracy are presented and evaluated. Comparisons of the methods reveal that the inventory inaccuracy problem can be effectively treated even without automatic product identification technologies in some situations.     

A note on joint optimization of maintenance and inventory

Previous work by Armstrong and Atkins examined age replacement and spare ordering decisions for a system which contained one machine subject to random failure and with only one spare machine in stock or on order at any one time. In this technical note we consider several extensions to that work which generalize the cost terms and the order lead time while retaining the one-machine one-spare structure of the original paper.     

An Improved formula for inventory decisions under service and safety stock constraints

This paper solves the reorder point inventory model under two constraints: safety stock is nonnegative, and the fraction of backorders does not exceed a given limit. The solution procedure modifies a noniterative approach due to Simpson in order to achieve better accuracy and wider applicability of the results. A formula for the implied cost of a fixed service level is also developed.     

基于供应链的企业库存成因及优化控制研究（二）

基于企业全面库存的管理思想,对库存成本、库存控制、库存系统优化等管理经验与前人研究成果进行分析,借鉴先进企业的库存管理理念和方法,以大型制造企业为核心研究对象,在集供应商、制造商、经销商为一体的供应链作为研究框架的基础上,运用供应链系统理论作为研究方法,分析了库存管理现状、影响因素及产生原因,从优化生产管理、整合企业内部供应链和跨企业供应链的角度提出了库存控制的相应对策,以实现全面库存优化,提高经营效益.     

基于供应链的企业库存成因及优化控制的研究（一）

基于企业全面库存的管理思想,对库存成本、库存控制、库存系统优化等管理经验与前人研究成果进行分析,借鉴先进企业的库存管理理念和方法,以大型制造企业为核心研究对象,在集供应商、制造商、经销商为一体的供应链作为研究框架的基础上,运用供应链系统理论作为研究方法,分析了库存管理现状、影响因素及产生原因,从优化生产管理、整合企业内部供应链和跨企业供应链的角度提出了库存控制的相应对策,以实现全面的库存优化,提高经营效益。     

Base stock versus WIP cap in single-stage make-to-stock production–inventory systems

A single-stage production-inventory system produces parts in a make-to-stock mode, and unsatisfied demand is backordered. The system operates under a so-called base stock with WIP cap replenishment policy, which works as follows. Whenever the Work-In-Process (WIP) plus finished goods inventory falls below a specified level, called base stock, a replenishment order for the production of a new part is issued. If the WIP inventory is below a different specified level, called WIP cap, the order goes through and a new part is released for production; otherwise, the order is put on hold until the WIP inventory drops below the WIP cap. First, it is shown that the optimal base stock that minimizes the long-run, average, inventory holding cost for a given minimum customer service level, is a non-increasing function of the WIP cap that reaches a minimum value, called minimum optimal base stock, at a finite WIP cap value, called critical WIP cap. Then, it is shown that the optimal WIP cap is less than or equal to the critical WIP cap and therefore the optima! base stock is greater than or equal to the minimum optimal base stock. More interestingly, however, it is conjectured that the optimal WIP cap is in fact exactly equal to the critical WIP cap and therefore the optimal base stock is exactly equal to the minimum optimal base stock. The minimum optimal base stock is none other than the optimal base slock of the same system operating under a classical base stock policy (with no WIP cap). Finally, the optimal parameters of a system operating under a base stock with WIP cap policy are related to the optimal parameter of the same system operating under a make-to-stock CONWIP policy.     

An integrated inventory optimization model for facility location-allocation problem

This paper presents an integrated inventory distribution optimisation model for multiple products in a multi-echelon supply chain environment. Inventory, transportation and location decisions are considered. The objective is to offer practical guideline to the steel retail supply chain practitioners in choosing the correct distribution centre, finding out inventory level at individual inventory keeping points (retailers and distribution centres) point thereby helping them in reducing overall distribution cost. The framework presented endorses systems approach and suggests near-optimal approach to calculating inventory for an individual distributor and his retailers. Two algorithms are used to solve this problem, a novel hybrid Multi-objective Self-learning particle swarm optimiser and Non-dominated sorting genetic algorithm-II. The model and solution methods are tested on real data-sets obtained from organisations in the steel retail environment. The actual data on inventory holding, ordering and transportation costs of distributors and retailers are used as inputs. The decisions like choosing correct set of Distribution centres, keeping optimal regular and safety stock inventory levels are arrived at by applying practical constraints in the supply chain. Model developed assists in effective and efficient distribution of the products manufactured from the optimal location at minimal cost.     

Dynamic programming algorithms for multi-stage safety stock optimization

The task of multi-stage safety stock optimization is very complex. Therefore, simplifying models with specific assumptions are considered. In this paper, the inventory system is controlled by a base-stock policy where each stockpoint of the inventory system follows a periodically reviewed order-up-to policy. End item demands are assumed to be normally distributed. To reduce the occurrences or size and duration of internal and external stockouts, appropriate service level constraints are specified for all items. Applying such a control policy within systems of serial, convergent or divergent structure, solution properties hold which reduce the solution set to a limited number of cut-levels. Dynamic programming allows to evaluate the relevant alternatives with little computational effort. For the serial system, both a forward and a backward recursion with different types of service levels are presented and extended to a backward algorithm for divergent and a forward algorithm for convergent systems. Bounds for the complexity of the algorithms are discussed and numerical examples are presented to demonstrate differences in size and allocation of safety stocks according to the prespecified type of service level.     

Optimal time policy for deteriorating items of two-warehouse inventory system with time and stock dependent demand and partial backlogging

We consider the problem of a two-warehouse inventory system under the effect of stock dependent demand. There are two warehouses to store the goods in which the first is rented warehouse and the second is own warehouse that deteriorates with two different rates. The aim of this study is to determine the optimal order quantity to maximize the profit of the projected model. Finally, some numerical examples and sensitivity analysis of parameters are made to validate the results of the proposed model.     

Joint optimization of maintenance and inventory policies for a simple system

We examine age replacement and ordering decisions for a system with only one component subject to random failure and with room for only one spare in stock. The system incurs costs for replacement, shortage, holding, and breakage; the lead time for receipt of an ordered spare is constant. We consider the solvability and desirability of jointly optimizing these two traditionally separate decisions. We show that the problem has some convexity properties that make it amenable to minimization. For our data set, we find that using separate optimization gives an average loss of 3% relative to the joint minimum; about a tenth of die time the difference was more than 10%, but in general this loss can vary from zero to arbitrarily large.     

Simultaneous optimization of production planning and inventory management of polyurethane foam plant

In this work, the management of a polyurethane foam plant is tackled through a mixed integer linear programming model that simultaneously solves production and inventory planning problems. The production process considers the foaming stage where large polyurethane blocks are produced as well as the curing step where the blocks are dried. The proposed formulation takes into account several tradeoffs involved in the overall production process. The daily production planning is tightly related to production requirements, available space for the curing and stored elements. Moreover, the required time to dry blocks introduces a delay that must be appropriately considered in order to allow an adequate operation of downstream operations. Thus, an integrated approach where all these problems are jointly addressed is proposed using a mathematical programming model. Several study cases provided by a local company are tested to demonstrate the model performance.     

Cost optimization for a single pass turning operation including inventory and penalty costs

This paper analyses total cost optimization for a single pass turning operation for a given feed and depth of out taking into consideration penalty cost for due date violation and in-process inventory cost. These costs are in addition to the two cost components, viz., machine and operator cost, and tool consumption cost, which are usually considered in studies on machining economics. In earlier work in machining economics, in-process inventory cost and penalty cost for due date violation have not been considered. Since these cost components are usually present in an industrial environment consideration of these costs makes the problem realistic.     

Simple evaluation of echelon stock (R,Q) policies for two-level inventory systems

A two-level inventory system with one warehouse and N retailers is considered. Leadtimes (transportation times) are constant, and the retailers face different compound Poisson demand processes. All facilities apply continuous review echelon stock (R, Q) policies with different reorder points and batch quantities. We provide a simple method for exact evaluation of holding and shortage costs.     

Joint optimization of preventive maintenance and inventory control in a production line using simulation

This paper proposes an integrated method for preventive maintenance and inventory control of a production line, composed of n machines (n?≥?1) without intermediate buffers. The machines are subject to failures and an age-dependent preventive maintenance policy is used. Approximate analytical results are proposed for the one machine case. Simulation software is used to model and simulate the behaviour of the production line of n machines under various maintenance and inventory control strategies. A methodology combining the simulation and genetic algorithms is proposed jointly to optimize maintenance and inventory control policies. Results are compared with the analytical solutions.     

Large-scale optimization methods applied to the cutting stock problem of irregular shapes

This paper describes a real feasibility study of applying large-scale optimization methods to the cutting stock problem of irregular shapes. We identify two approaches for minimizing waste in the cutting stock problem of irregular shapes: better packing and better scheduling of cuts. This paper is concerned with the scheduling problem only. By scheduling of cuts we mean deciding which combination of parts to group together on the cutting table so that overall material needed by all cuts is minimized. Such a problem usually requires considering many combinations. However, with the development of various feasibility requirements imposed on the column generation process this number can be reduced considerably. Furthermore, the introduction of interior-point algorithms for linear programming by Karmarkar in 1984, allows the consideration of much larger linear programming problems than was possible just a few years ago.     

数据挖掘与最优化结合的理论方法体系与问题求解模型

在研究了已有数据挖掘的过程模型的基础上,提出了数据挖掘与最优化结合的理论方法体系和支持最终决策分析的管理问题求解模型,目标是有效地将各种数据挖掘技术与最优化方法在实际应用中有机地结合起来,并为复杂的管理决策分析问题求解和决策实施提供一个切实可行的参考模型。通过在客户群决策分析中的应用,验证了提出的方法和模型的可行性和有效性。     

Spare parts stock control for redundant systems using reliability centered maintenance data

In the classical approach to determine how many spare parts to stock, the spare parts shortage costs or the minimum fill rate is a key factor. A difficulty with this approach lies in the estimation of these shortage costs or the determination of appropriate minimum fill rates. In an attempt to overcome this problem, we propose to use the data gathered in reliability centered maintenance (RCM) studies to determine shortage costs. We discuss the benefits of this approach. At the same time, the approach gives rise to complications, as the RCM study determines downtime costs of the underlying equipment, which have a complex relation with the shortage cost for spare parts in case multiple pieces of equipment have different downtime costs. A further complication is redundancy in the equipment. We develop a framework that enables the modeling of these more complicated systems. Based on the framework, we propose an approximative, analytic method that can be used to determine minimum stock quantities in case of redundancy and multiple systems. In a quantitative study we show that the method performs well. Moreover, we show that including redundancy information in the stocking decision gives significant cost benefits.     

数据网格资源选择优化模型

为了满足网格数据服务的可靠性和传输时间约束,同时兼顾网络负载及节点资源的有效利用,提出了一种网格数据资源选择优化模型,该模型以网络负载和资源代价为优化目标函数,以节点的传输速度、可靠性、传输距离、网络状态、客户端带宽和容忍度阈值为输入,进而决策出参与服务的最优节点集合,同时模型中设定了权重因子来均衡网络负载与资源代价....