Optimal policy for a dynamic,non-stationary,stochastic inventory problem with capacity commitment

This paper studies a single-product, dynamic, non-stationary, stochastic inventory problem with capacity commitment, in which a buyer purchases a fixed capacity from a supplier at the beginning of a planning horizon and the buyer’s total cumulative order quantity over the planning horizon is constrained with the capacity. The objective of the buyer is to choose the capacity at the beginning of the planning horizon and the order quantity in each period to minimize the expected total cost over the planning horizon. We characterize the structure of the minimum sum of the expected ordering, storage and shortage costs in a period and thereafter and the optimal ordering policy for a given capacity. Based on the structure, we identify conditions under which a myopic ordering policy is optimal and derive an equation for the optimal capacity commitment. We then use the optimal capacity and the myopic ordering policy to evaluate the effect of the various parameters on the minimum expected total cost over the planning horizon.     

Optimal Ordering Policies for Inventory Systems with Emergency Ordering

This paper considers dynamic single- and multi-product inventory problems in which the demands in each period are independent and identically distributed random variables. The problems considered have the following common characteristics. At the beginning of each period two order quantities are determined for each product. A “normal order” quantity with a constant positive lead time of λ _n periods and an “emergency order” quantity with a lead time of λ _e periods, where λ _e = λ _n - 1. The ordering decisions are based on linear procurement costs for both methods of ordering and convex holding and penalty costs. The emergency ordering costs are assumed to be higher than the normal ordering costs. In addition, future costs are discounted.For the single-product problem the optimal ordering policy is shown to be the same for all periods with the exception of the last period in the N-period problem. For the multi-product problem the one- and N-period optimal ordering policy is characterized where it is assumed that there are resource constraints on the total amount that can be ordered or produced in each period.     

Two-product inventory management with fixed costs and supply uncertainty

This paper determines the optimal ordering policy for a two-product, periodic-review inventory problem in which the probability of supply availability is unknown. Moreover, there are two different fixed costs assigned to each product. Demand rates are random variables with known probability density functions, and the supply availability for each product is updated at the beginning of each time period. We prove the optimality of (s,S) policy with a monotone switching curve that indicates the priority of production, where the order-up-to levels and the reorder points are functions of supply availability information. A simple computation is proposed to calculate the two threshold levels. Bayesian updating helps to manage the optimal ordering policy by updating supply disruption information. Numerical results show that improving the accuracy of the forecast leads to making a better ordering decision and eliminating the negative effect of supply disruption on the total cost.     

Inventory control by different service levels

This paper examines the multiple period inventory control problem of a single product with multiple (two) prices, depending on service level, in which optimal pricing and ordering decisions are made in each period. Traditional inventory and pricing models consider only single products, single prices, and single service levels. However, this research paper finds that a seller can improve inventory control and revenue by offering multiple prices depending on service level. This research considers a single product with multiple (two) pricing policies corresponding to service level as follows: if the customer is willing to delay the shipment, he/she will be offered a lower regular price. Otherwise, the customer will pay the regular price plus extra charges for express service. In this paper, I show the following: (1) there is an optimal pricing and replenishment policy that can control inventory and (2) there exists a finite threshold for inventory levels such that if the inventory level at the beginning of each period is higher than the threshold, the customer will be offered the express service at the regular price, without any extra charge.     

A note on inventory policies for products with residual-life-dependent demand

We study inventory ordering policies for products that attract demand at a decreasing rate as they approach the end of their usable lifetime, for example, perishable items nearing expiration. We consider the “product freshness’’, or equivalently, the time until expiration (“residual life”) as a factor influencing the customer demand. In a profit-maximizing framework, we build on the Economic Order Quantity (EOQ) replenishment model and formulate the inventory ordering problem using a deterministic demand function that is concave decreasing in the the age of the product. We provide analytical results on the optimal ordering policy, including an explicit characterization of the decisions in the linear-demand case, and we develop an easy-to-implement adaptive heuristic policy for the general case. Numerical examples show that the optimal policy generates significant profit gains compared to the traditional cost-based policies and the adaptive heuristic policy performs highly satisfactorily in the tested instances.     

Production planning with approved vendor matrices for a hard-disk drive manufacturer

We develop an optimal production schedule for a manufacturer of hard-disk drives that offers its customers the approved vendor matrix (AVM) as a competitive advantage. An AVM allows each customer to pick and choose the various product component vendors for individual or pairs of components constituting their product. The production planning problem faced by the manufacturer is to meet customer demand as precisely as possible while observing the matrix restrictions and also the limited availability of production resources. We formulate this problem as a linear programming model with a large number of variables, and present a solution procedure based on the column generation technique. A special class of the problem is then studied, whereby the number of production setups in each period is limited and discrete. We modify our formulation into a mixed-integer problem, and proceed to develop procedures that can obtain good feasible solutions using linear programming rounding techniques.     

Coordinating supply chain inventories through common replenishment epochs

This paper proposes a model to study and analyze the benefit of coordinating supply chain inventories through the use of common replenishment epochs or time periods. A one-vendor, multi-buyer supply chain for a single product is analyzed. Under the proposed strategy, the vendor specifies common replenishment periods and requires all buyers to replenish only at those time periods. The vendor offers a price discount to entice the buyers to accept this strategy. The optimal replenishment period and the price discount to be offered by the vendor are determined as a solution to a Stackelberg game. After developing a method to solve the game, a numerical study is conducted to evaluate the benefit of the proposed coordinated strategy.     

Mathematical modelling for determining economic batch size and optimal number of deliveries for EPQ model with quality assurance

The classic economic production quantity (EPQ) model assumes a continuous inventory-issuing policy for satisfying product demand and a perfect production for all items produced. However, in a real-life vendor–buyer integrated system, a multi-delivery policy is often used in lieu of continuous issuing policy and it is inevitable to generate defective items during a production run. This study addresses these issues by incorporating multiple deliveries of the finished batch, customer's inventory-holding cost and manufacturer's quality assurance cost into an EPQ model with the imperfect reworking of random defective items. Mathematical modelling and analyses are employed. Convexity of the long-run expected cost function is proved by the use of Hessian matrix equations, and the closed-form solutions in terms of the optimal lot size and optimal number of deliveries are obtained. The research results are demonstrated with a numerical example with a discussion on its practical usage.     

带短期价格折扣和允许两次特殊补货的库存决策模型

针对供应商提供短期价格折扣且允许零售商两次特殊补货的库存系统, 建立了以零售商库存效益最大化为目标的库存决策模型, 分析了模型的性质, 根据经济订单批量补货决策下补货时间点与折扣时段的关系, 确定了零售商在不同补货策略下的库存效益增值函数. 据此给出零售商相应的最优补货策略函数表达式, 提出了该模型的一个全局优化算法, 并通过数值算例验证了模型和算法的有效性与可行性.     

LIFO Distribution Systems

The regional distribution problem for a perishable product is examined, under the important assumption that younger units are issued first (LIFO) to satisfy the demands of the customers at the locations. Optimal and approximately optimal allocation policies for two alternative distribution systems are derived. Their properties are discussed, and comparisons are made with the equivalent policies in a FIFO environment.     

Joint pricing and inventory control with a Markovian demand model

We consider the joint pricing and inventory control problem for a single product over a finite horizon and with periodic review. The demand distribution in each period is determined by an exogenous Markov chain. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. The surplus costs as well as fixed and variable costs are state dependent. We show the existence of an optimal (s, S, p)-type feedback policy for the additive demand model. We extend the model to the case of emergency orders. We compute the optimal policy for a class of Markovian demand and illustrate the benefits of dynamic pricing over fixed pricing through numerical examples. The results indicate that it is more beneficial to implement dynamic pricing in a Markovian demand environment with a high fixed ordering cost or with high demand variability.     

考虑供应商服务与零售商退货的定价博弈分析

研究由一个供应商和一个零售商组成的二级供应链,由供应商提供产品服务,零售商制定产品零售价,在一个销售周期结束后存在零售商向供应商的退货,退货产生的物流成本由零售商与供应商通过博弈的方式共同分担.基于博弈理论,建立了供应商和零售商以各自利润最大化为目标,以服务水平、零售价和退货为主要影响因素的Nash和Stackelberg博弈.采用数值方法,对这两个博弈进行了求解.得到供应商为零售商分担退货物流成本最优比例、供应商最优服务水平和零售商最优定价策略.研究表明,Nash博弈时的解是唯一的,此时供应商不会分担退货物流成本;Stackelberg博弈时,供应商分担退货物流成本比例依据批发价大小而定.     

Profit maximization in an inventory system with time-varying demand,partial backordering and discrete inventory cycle

In this paper, an inventory problem where the inventory cycle must be an integer multiple of a known basic period is considered. Furthermore, the demand rate in each basic period is a power time-dependent function. Shortages are allowed but, taking necessities or interests of the customers into account, only a fixed proportion of the demand during the stock-out period is satisfied with the arrival of the next replenishment. The costs related to the management of the inventory system are the ordering cost, the purchasing cost, the holding cost, the backordering cost and the lost sale cost. The problem is to determine the best inventory policy that maximizes the profit per unit time, which is the difference between the income obtained from the sales of the product and the sum of the previous costs. The modeling of the inventory problem leads to an integer nonlinear mathematical programming problem. To solve this problem, a new and efficient algorithm to calculate the optimal inventory cycle and the economic order quantity is proposed. Numerical examples are presented to illustrate how the algorithm works to determine the best inventory policies. A sensitivity analysis of the optimal policy with respect to some parameters of the inventory system is developed. Finally, conclusions and suggestions for future research lines are given.

     

Analysis and design of returns policies from a supplier's perspective

This paper considers the problem of designing a returns policy in a supply chain from a supplier's perspective. The supply chain considered here is assumed to have one supplier and one retailer who serves a random demand of a product with a short life cycle. The retailer can return all the unsold products to the supplier with a partial refund. We found that if the retailer behaviour is rational, that is, ordering the optimal quantity to maximize its expected profit, then both retailer and supplier could benefit from the returns policy. Furthermore, we established that the optimal buyback price is independent of the mean of the random demand, but the variance of the demand has a significant impact on setting the optimal buyback price. The higher the variance the higher the optimal buyback price and the larger the profit gain of both parties. Numerical studies are employed to help understand the benefits of returns policies for the supplier, the retailer, and the whole supply chain.     

Optimal periodic replacement policy for repairable products under free-repair warranty

This paper investigates the effects of a free-repair warranty on the periodic replacement policy for a repairable product. Cost models are developed for both a warranted and a non-warranted product, and the corresponding optimal periodic replacement policies are derived such that the long-run expected cost rate is minimized. For a product with an increasing failure rate function, structural properties of these optimal policies are obtained. By comparing these optimal policies, we show that the optimal replacement period for a warranted product should be adjusted toward the end of the warranty period. Finally, examples are given to numerically illustrate the impact of a product warranty on the optimal periodic replacement policy.     

Optimal ordering and pricing policy for an inventory system with trial periods

It is a business practice that home shopping companies offer a free trial period for their products with a goal of increasing sales. Under this policy, if for any reason customers are not satisfied with the purchase, they can return the product for a refund within the trial period. To develop inventory strategies in such environment, home shopping companies should take the return phenomenon into account so as to increase their profit. This paper considers this phenomenon and develops a seasonal inventory model to deal with the problem. Two scenarios are analyzed. In the first scenario, demand is assumed to be linearly price-dependent while in the second one, it is assumed to be exponentially price-dependent. The purpose of this research is to maximize the total profit over a given planning period by determining the optimal ordering quantity and price. The analytical results demonstrate that the optimal ordering quantity and prices are obtained using closed-form formulas.     

Optimal policy for a two-facility inventory problem with storage constraints and two freight modes

This paper considers a two-facility supply chain for a single product in which facility 1 orders the product from facility 2 and facility 2 orders the product from a supplier in each period. The orders placed by each facility are delivered in two possible nonnegative integer numbers of periods. The difference between them is one period. Random demands in each period arise only at facility 1. There are physical storage constraints at both facilities in each period. The objective of the supply chain is to find an ordering policy that minimizes the expected cost over a finite horizon and the discounted stationary expected cost over an infinite horizon. We characterize the structure of the minimum expected cost and the optimal ordering policy for both the finite and the discounted stationary infinite horizon problems.     

Stochastic Multiproduct Inventory Models with Limited Storage

This paper studies multiproduct inventory models with stochastic demands and a warehousing constraint. Finite horizon as well as stationary and nonstationary discounted-cost infinite-horizon problems are addressed. Existence of optimal feedback policies is established under fairly general assumptions. Furthermore, the structure of the optimal policies is analyzed when the ordering cost is linear and the inventory/backlog cost is convex. The optimal policies generalize the base-stock policies in the single-product case. Finally, in the stationary infinite-horizon case, a myopic policy is proved to be optimal if the product demands are independent and the cost functions are separable.     

A solution approach to the inventory routing problem in a three-level distribution system

We consider the infinite horizon inventory routing problem in a three-level distribution system with a vendor, a warehouse and multiple geographically dispersed retailers. In this problem, each retailer faces a demand at a deterministic, retailer-specific rate for a single product. The demand of each retailer is replenished either from the vendor through the warehouse or directly from the vendor. Inventories are kept at both the retailers and the warehouse. The objective is to determine a combined transportation (routing) and inventory strategy minimizing a long-run average system-wide cost while meeting the demand of each retailer without shortage. We present a decomposition solution approach based on a fixed partition policy where the retailers are partitioned into disjoint and collectively exhaustive sets and each set of retailers is served on a separate route. Given a fixed partition, the original problem is decomposed into three sub-problems. Efficient algorithms are developed for the sub-problems by exploring important properties of their optimal solutions. A genetic algorithm is proposed to find a near-optimal fixed partition for the problem. Computational results show the performance of the solution approach.     

Raw materials and production control with random supply and demand,an outside market and production capacity

We study a capacitated periodic inventory review problem in which the optimal control of both raw materials and finished product inventories simultaneously involves optimal decisions on materials purchasing from suppliers, buying or selling of materials in spot market, and production quantity in each period. We found that the dynamic program model of the problem is decomposable, and there is an independent relationship between the decisions on materials purchasing/selling and finished product production. Optimal policies are characterized and extensions are discussed.