The Trended Inventory Lot Sizing Problem with Shortages Under a New Replenishment Policy

In the past few years, considerable attention has been given to the inventory lot sizing problem with trended demand over a fixed horizon. The traditional replenishment policy is to avoid shortages in the last cycle. Each of the remaining cycles starts with a replenishment and inventory is held for a certain period which is followed by a period of shortages. A new replenishment policy is to start each cycle with shortages and after a period of shortages a replenishment should be made. In this paper, we show that this new type of replenishment policy is superior to the traditional one. We further propose four heuristic procedures that follow the new replenishment policy. These are the constant demand approximation method, the equal cycle length heuristic, the extended Silver approach, and the extended least cost solution procedure. We also examine the cost and computation time performances of these heuristic procedures through an empirical study. The number of test problems solved to optimality, average and maximum cost deviation from optimum were used as measures of cost performance. The results of the 10 000 test problems reveal that the extended least cost approach is most cost effective.     

A Note on the Heuristic for Replenishment of Trended Inventories Considering Shortages

We discuss the inventory replenishment policy for an item having a deterministic demand pattern with a linear (positive) trend and shortages. A heuristic is developed to determine the decision rule for selecting the times and sizes of replenishments over a finite time-horizon so as to keep the total costs minimum. The use of the heuristic is illustrated with a numerical example.     

The Inventory Lot-Sizing Problem with Continuous Time-Varying Demand and Shortages

In this study, we develop and analyse an optimal solution procedure for the inventory lot-sizing problem with a general class of time-varying demand functions. The objective of the procedure is to determine the optimal replenishment schedule over a finite planning horizon during which shortages are allowed and are completely backordered. We show that the procedure yields a unique optimal replenishment schedule for both increasing and decreasing demand patterns. We also discuss two particular cases of linear and non-linear demand trend models, and we illustrate the optimal solution procedure with four numerical examples.     

The Wiener Sequential Testing Problem with Finite Horizon

We present a solution of the Bayesian problem of sequential testing of two simple hypotheses about the mean value of an observed Wiener process on the time interval with finite horizon. The method of proof is based on reducing the initial optimal stopping problem to a parabolic free-boundary problem where the continuation region is determined by two continuous curved boundaries. By means of the change-of-variable formula containing the local time of a diffusion process on curves we show that the optimal boundaries can be characterized as a unique solution of the coupled system of two nonlinear integral equations.     

An Inventory Model with Finite Horizon and Price Changes

An inventory model is developed for a finite horizon and price changes. The structure and form of the optimal policy is determined along with sensitivity analysis with respect to the length of the horizon. This is a prelude to considering an infinite horizon problem in which at some a priori known time the purchase price of the item will increase. In this paper appropriate ordering policies are determined with respect to known information about an ensuing price rise.     

Computing a Stationary Base-Stock Policy for a Finite Horizon Stochastic Inventory Problem with Non-linear Shortage Costs

Abstract

We consider a periodic-review stochastic inventory problem in which demands for a single product in each of a finite number of periods are independent and identically distributed random variables. We analyze the case where shortages (stockouts) are penalized via fixed and proportional costs simultaneously. For this problem, due to the finiteness of the planning horizon and non-linearity of the shortage costs, computing the optimal inventory policy requires a substantial effort as noted in the previous literature. Hence, our paper is aimed at reducing this computational burden. As a resolution, we propose to compute “the best stationary policy.” To this end, we restrict our attention to the class of stationary base-stock policies, and show that the multi-period, stochastic, dynamic problem at hand can be reduced to a deterministic, static equivalent. Using this important result, we introduce a model for computing an optimal stationary base-stock policy for the finite horizon problem under consideration. Fundamental analytic conclusions, some numerical examples, and related research findings are also discussed.     

Alternative Solution Methods for the Inventory Replenishment Problem under Increasing Demand

Two solution methods are offered for the no-shortage stock control problem under linearly increasing demand. The heuristic of the first "myopic" method is also exploited in the second method, which is based on a dynamic programming formulation. The DP formulation is not only trivial to solve computationally, but also offers ready-made sensitivity analyses. Unlike the other method, it also readily extends to more complicated models.     

A Note on a Replenishment Policy for an Inventory Model with Linear Trend in Demand and Shortages

The present paper deals with an alternative approach for finding the optimal number of replenishments and optimal replenishment times for a finite-horizon inventory problem with linearly increasing demand allowing shortages which are fully backlogged. The method is developed by assuming that successive replenishment cycle lengths are in arithmetic progression. The corresponding results in the absence of shortage are also derived and finally some numerical examples are presented and compared with the existing methods to test the accuracy and effectiveness of the method. A sensitivity analysis has also been presented to study the effect of changes in the system parameters on the optimal cost.     

有限时区上的最优转换和停止问题

讨论了有限时区上的最优转换和停止问题,它是一类同时具备脉冲控制和最优停止特征的最优控制问题.问题的最优值以及最优转换和停止决策可以由具有混合障碍的多维反射倒向随机微分方程的解来刻画.接着考虑了形式更一般的反射倒向随机微分方程并证明了方程解的存在唯一性.     

有限时区上的最优转换和停止问题

讨论了有限时区上的最优转换和停止问题,它是一类同时具备脉冲控制和最优停止特征的最优控制问题.问题的最优值以及最优转换和停止决策可以由具有混合障碍的多维反射倒向随机微分方程的解来刻画.接着考虑了形式更一般的反射倒向随机微分方程并证明了方程解的存在唯一性.     

On an Inventory Model for Deteriorating Items With Increasing Time-varying Demand and Shortages

In this paper we present an exact solution for the inventory replenishment problem with shortages, in which items are deteriorating at a constant rate. The demand rates are increasing with time over a known and finite planning horizon. We also present a dynamic programming solution to the problem. Both these methods provide a net improvement over existing methods.     

Inventory Replenishment Policies — Computational Solutions

Relatively minor changes in the assumptions associated with the classical deterministic models for inventory control can give rise to models which are difficult or impossible to analyse by analytical means.A low-cost computational procedure is outlined and applied to two such models associated with the no-shortage policy. The situations examined involve trends in demand and linear inflation in costs.     

Inventory Replenishment Policy for Cyclic Demand

We consider optimal replenishment policy in the case of deterministic demand, with demand a known function which is periodic in time. The general formulation is a special case of Donaldson's fixed-horizon model, and two common situations are discussed: (i) demand varies sinusoidally; and (ii) there is an abrupt increase or decrease in demand, represented mathematically by a discontinuity in the demand rate.     

联合订货下基于ø-散度的多产品库存鲁棒优化模型

针对多产品联合库存决策问题,在市场需求不确定条件下,建立了考虑联合订货成本的多产品库存鲁棒优化模型。针对不确定市场需求,采用一系列未知概率的离散情景进行描述,给出了基于最小最大准则的鲁棒对应模型,并证明了(s,S)库存策略的最优性。进一步,在仅知多产品市场需求历史数据基础上,采用基于ø-散度的数据驱动方法构建了满足一定置信度要求的关于未知需求概率分布的不确定集。在此基础上,为获得(s,S)库存策略的相关参数,运用拉格朗日对偶方法将所建模型等价转化为易于求解的数学规划问题。最后,通过数值计算分析了Kullback-Leibler散度和Cressie-Read散度以及不同的置信水平下的多产品库存绩效,并将其与真实分布下应用鲁棒库存策略得到的库存绩效进行对比。结果表明,需求分布信息的缺失虽然会导致一定的库存绩效损失,但损失值很小,表明基于文中方法得到的库存策略能够有效抑制需求不确定性扰动,具有良好的鲁棒性。     

Inventory Replenishment Policy for Increasing Demand

The Donaldson model for inventory replenishment is investigated for a general class of increasing demands. In particular, it is shown that the system of reorder times is uniquely specified and well-behaved when the demand f(t) is log-concave, i.e. the derivative of log f(t) is a decreasing function of time. In addition, a numerical procedure is outlined which will produce the set of optimal times at which to re-order, provided the demand f(t) is of sufficiently simple form, for example a simple power law or exponential demand.     

Joint Replenishment in Multi-Item Inventory Systems

A multi-item inventory system is considered which has the property that, for each single item, a reorder policy using the E.O.Q. formula would be appropriate. Holding costs are linear, and fixed ordering costs are assumed to be composed of a major set-up cost reflecting the pure fact of placing an order, and a sum of minor set-up costs corresponding to the items included in the order. If it is desirable to form a certain number of groups of items where all items of one group share the same order cycle, it is shown that there is always an optimal grouping in which items are arranged in increasing order of their ratio of yearly holding costs and minor set-up costs.A heuristic for forming the groups is given which turns out to be an optimal algorithm for the case that there are no major set-up costs. After an initial sorting of ratios, the worst-case complexity of this procedure is linear in the number of items.