Consignment stock inventory policy: methodological framework and model

We consider the hierarchical coordinated control of a multi-procedure conveyor-serviced production station system with flexible stations deployed between adjacent procedures, which includes a dynamic intra-procedure switching control of the flexible stations for the goal of balancing different procedures and a dynamic inter-procedure production coordination of all of the stations within each procedure. It is complicated in terms of modelling and optimisation, and thus, it is difficult to find a solution using numerical methods; as a result, we refer to model-free learning optimisation methods. First, we establish a neuro-dynamic programming algorithm by utilising cerebellar model articulation controllers (CMACs) to approximate state-action values at an upper hierarchy. Second, according to the reaction-diffusion phenomenon, we combine a Wolf-PHC algorithm with a local information-interaction scheme to learn look-ahead control policies at the lower hierarchy. Simulation results show that, compared with traditional Q-learning and the backward Q-learning based Q-learning, our proposed CMAC-based learning optimisation methods have the advantages of yielding a higher processing rate and having a faster optimisation speed with a lower storage requirement.     

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.     

基于横向转运策略的多级库存配置建模与优化

在多级维修供应体系下,采用备件横向转运补给策略能有效提高装备保障效率,针对该问题,依据生灭过程和METRIC理论,建立了多等级多层级装备备件的库存协调转运模型,并采用一种启发式算法对模型进行求解。在此基础上以装备可用度为约束,备件购置费用最低为目标,利用边际算法对库存方案进行优化。通过实例,模型的正确性通过仿真方法得到了验证,并与非转运条件下的优化方案比较,结果表明,本文构建的转运模型在提高装备保障效能方面明显优于非转运模型。     

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.     

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 inventory management approximation for estimating aggregated regional food stock levels

Food is an important resource in disaster management, and food stock levels hold significance for disaster mitigation research and practice. The presence or absence of food stocks is a vulnerability indicator of a region. A large part of overall food stock, before a disaster strikes, is held by private companies (retailers, wholesalers and food producers). However, there is little-to-no information on the food stock levels of commercial companies, and no approach exists to derive such information. We develop an approximation model based on essential inventory management principles and available data sources to estimate aggregated food stock levels in supply networks. The model is applied in a case example that features dairy product stock levels in the German state of Saxonia. The resulting overall stock levels are normalised, and their usability is showcased in a simple vulnerability analysis. Disaster managers are provided with a model that can be used estimate otherwise unavailable data and facilitates investigations into the regional resilience of an area. The limitations of our study are based on the aggregated nature of the supply network structure and data usage (i.e. in the model, we do not consider any seasonality or trend effects).     

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.     

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.     

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.     

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.     

Cutting the double loop: Theory and algorithms for reliability-based design optimization with parametric uncertainty

Parametric uncertainties complicate engineering design—confounding regulated design approaches and degrading the performance of reliability efforts. The simplest means to tackle this uncertainty is double-loop simulation , a nested Monte Carlo method that, for practical problems, is intractable. In this work, we introduce a flexible, general approximation technique that obviates the double loop. This approximation is constructed in the context of a novel theory of reliability design under parametric uncertainty: we introduce metrics for measuring the efficacy of reliability-based design optimization strategies ( epistemic design gap and effective reliability ), minimal conditions for controlling uncertain reliability ( precision margin ), and stricter conditions that guarantee the desired reliability at a designed confidence level. We provide a number of examples with open-source code to demonstrate our approaches in a reproducible fashion.     

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.