The resource constrained single-item inventory problem with demand-dependent unit cost

In this paper, we present an economic order quantity (EOQ) with both demand-dependent unit cost and restrictions. An analytical solution of the EQO is derived using a recent and simple method, which isthe geometric programming approach. The EOQ inventory model with demand-dependent unit cost without any restriction and the classical EOQ inventory model are obtained.     

An optimal replenishment model for inventory items with normally distributed deterioration

This paper deals with the inventory replenishment problem for deteriorating items with normally distributed shelf life, continuous time-varying demand, and shortages under the inflationary and time discounting environment. The reasons of choosing normal are twofold: it is one of the most important probability phenomena in the real world due to the classical central limit theorem, and it is also one of the most commonly used lifetime distributions in reliability contexts. The problem is formulated as a dynamic programming model and solved by numerical search techniques. The solutions of the model determine the optimal replenishment schedule over a finite planning horizon so that the present worth of the future costs associated with the system is minimized. In the extensive experiments, we validate the model, demonstrate the optimal replenishment schedule and lot-size, and carry out a comparative study to ascertain its contribution. In addition, sensitivity analysis was provided to help identify the most crucial factors that affect system performance. The experimental result shows that the deteriorating problem solved by an appropriate model (i.e. the proposed normal model) can save the total cost up to 2% approximately. It also identifies that the magnitudes of purchase cost per unit and demand rate are the most significant parameters that affect the replenishment decisions and cost.     

The resource constrained multi-item inventory problem with price discount: a geometric programming approach

In this paper we present a geometric programming approach for determining the inventory policy for multiple items having price discount and a limit on the total average inventory of all the items. An example is solved to illustrate the method.     

Postponement implementation in integrated production and inventory plan under deterioration effects: a case study of a juice producer with limited storage capacity

Abstract

The aim of this study is to develop a production and inventory plan for a fresh apple juice producer. During harvest season, the producer extracts premium juice from freshly picked apples and keeps an inventory of these premium apples in his temperature-controlled storage facility. The producer extracts also regular juice from regular apples purchased from third-party storages. To satisfy future demand, the producer carries inventories of juice and apple. The levels of apple inventories are constrained by the producer’s limited storage space, but he can replenish regular apples. To assist the producer in facing demand uncertainty and deterioration of apples, we develop a production and inventory plan that incorporates postponement to mitigate demand uncertainty. As postponement decisions are shaped by the cost structure of inventories, we integrate in one model the postponement decisions and the deterioration mitigation decisions that can alter the inventory costs. We build multi-period stochastic programming with recourse model to determine juice batch sizes and apple inventories that maximize the producer’s expected profit. The optimal solution illustrates the use of time and form postponements. We discuss the interactions between postponement implementation and decisions to mitigate apples deterioration. We compare the production and inventory plans with and without postponement and with and without apple deterioration. We also present sensitivity analyses for the plan under varying inventory cost and storage space.     

Multi-item production lot-size inventory model with varying order cost under a restriction: A geometric programming approach

In this paper we present a geometric programming approach for determining the inventory policy for multiple items having varying order cost, which is a continuous function of the order quantity, and a limit on the total average inventory of all items. Our model is a generalization of that of Gupta and Gupta for unrestricted single-item order quantity model with varying order cost and assumes the same order cost function. This cost function relates well to real-life situations since it increases as the order quantity increases and, at the same time, it is easy to handle when deducing previous work as special cases of our model since it is easily reducible to a constant. An example is solved to illustrate the method.     

A new MRP/GT lot sizing heuristic: A simulation study

This paper studies the lot-sizing problem in Material Requirements Planning/Group Technology (MRP/GT) systems. A GT production cell is designed to produce many families of components. A major setup is required when switching from manufacturing one family of components to another family, and a minor setup is needed when switching from manufacturing a component type to another component type within the same family. Inventory holding cost is incurred if inventory level is positive, and inventory shortage cost is incurred if inventory level is negative, that is, backordering. The objective of the proposed lot-sizing problem is to minimize the sum of major and minor setup costs, holding and shortage costs, and regular production cost, and to meet simultaneously the demand requirements. The proposed problem is modelled into a linear integer program, a heuristic method to solve the problem is proposed, and a simulation experiment conducted to evaluate the performance of the proposed heuristic and some existing heuristics. The computational results show that the proposed heuristic is useful to reduce the total cost significantly over a wide variety of simulated environments.     

An optimal product-reconfiguration policy due to order changes

Abstract

It is not an uncommon problem that a finished product cannot be delivered to its customer due to order change. In many real-life applications, such as rack-mounted computer products, it is possible to reconfigure a product by altering the combination of its components. Therefore, an inventory item, resulting from a cancelled order, can be handled in one of two ways: (1) keep the product in storage for a future order; or (2) send the product back to the manufacturing Door for reconfiguration in accordance with a new order A wise decision can be made by evaluating the trade-off between the inventory cost and the conversion cost. This paper presents an optimization procedure for achieving the minimum-cost solution. The problem is formulated by a quadratic programming model. Under a fairly general condition, the problem can be converted into a standard capacitated transportation problem and, therefore, can be solved efficiently. The cost structure, problem formulation, and solution technique arc discussed.     

短生命周期产品的三种库存模型的比较

讨论短生命周期产品库存模型,考虑无形变质因素,并假定无形变质率与需求率成反比关系.在线性需求和常数生产率的条件下,假设,若需求率为1,则视作产品的市场生命周期结束.并且,在产品生命周期的前期不存在缺货的情况下,给出了短生命周期产品分别在理想状态、允许缺货以及价格折扣导致需求率变化等3种状态下的库存模型,最后在相同参数条件下对这3种模型进行比较,找出了单位时间内平均总成本最小的最优库存模型,厂商可以根据自身的情况选择合适的库存策略.     

Heuristic for scheduling in a two-machine bicriteria dynamic flowshop with setup and processing times separated

This paper addresses the two-machine bicriteria dynamic flowshop problem where setup time of a job is separated from its processing time and is sequenced independently. The performance considered is the simultaneous minimization of total flowtime and makespan, which is more effective in reducing the total scheduling cost compared to the single objective. A frozen-event procedure is first proposed to transform a dynamic scheduling problem into a static one. To solve the transformed static scheduling problem, an integer programming model with N ² + 5N variables and 7N constraints is formulated. Because the problem is known to be NP-complete, a heuristic algorithm with the complexity of O (N ³) is provided. A decision index is developed as the basis for the heuristic. Experimental results show that the proposed heuristic algorithm is effective and efficient. The average solution quality of the heuristic algorithm is above 99%. A 15-job case requires only 0.0235 s, on average, to obtain a near or even optimal solution.     

多品种集约生产计划问题的模糊方法

提出具有模糊需求量和模糊能力约束以及资本水平约束的多品种类集约生产计划问题 的模糊优化模型及模糊解方法. 通过对模糊需求量和模糊等式的描述,提出了模糊需求环境下 生产- 库存平衡方程的两种等价的描述方法, 并给出了模糊等式的实用解释. 建立了具有模 糊需求量和模糊能力约束集约生产计划问题的优化模型FMAPP ,并给出了求解模型的参数规 划方法.     

Emergency inventory ordering assuming Poisson demands

Abstract

Most business and industrial firms use some procedure for emergency ordering. If independent demand for low-volume, high-cost items is Poisson distributed, subsequent analyses reveal that emergency ordering may be less expensive than carrying extra safety stock. Emergency ordering reduces the out-of-stock cost as well as the required safety stock. Total cost is sensitive to the lead time required for emergency orders. The results are particularly applicable to maintenance inventory. Under the assumptions of this study, the conclusion may be drawn that an emergency ordering system may approach the theoretical minimum for operating an inventory system.     

持有成本和变质率时变的非立即变质品库存策略

本文主要研究非立即变质品的库存策略设计问题。以平均利润最大化为决策目标,构建了一个一般化的库存模型,假设需求受即时库存水平影响且在保鲜期和变质期内库存水平对需求的影响系数不同,持有成本和变质期内的变质率均随时间发生变化,系统允许缺货且短缺量部分延迟订购。进一步证明了当参数满足一定条件时,模型存在唯一的最优解。最后,采用牛顿法给出一些具体的数值算例,并对模型中主要参数的灵敏度进行了分析。结果显示:延长物品的保鲜期将有助于增加系统的平均利润;增加变质期内的需求比增加保鲜期内的需求更有利于增加系统的平均利润;对于变质率高的产品来说,其变质处理成本对最优策略和平均利润的影响不容忽视。此外,本文所构建的模型具有一般性,因此,其应用范围更加广泛。     

A simulation-based multi-objective optimization framework: A case study on inventory management

We propose a simulation-based solution framework for tackling the multi-objective inventory optimization problem. The goal is to find appropriate settings of reorder point and order quantity to minimize three objective functions simultaneously, which are the expected values of the total inventory cost, the average inventory level, and the frequency of inventory shortage. We develop new algorithms that can exploit statistically valid ranking and selection (R&S) procedures and the desirable mechanics of conventional multi-objective optimization techniques. Two simulation algorithms are proposed to be applied in different scenarios depending on the preference information that is revealed either during or after the actual optimization process. Experimental results are provided to evaluate the efficiency of the developed algorithms and other existing solution frameworks.     

A mixed inventory model with variable lead time and random supplier capacity

In this paper, we have studied analytically the implication of a controllable lead-time and a random supplier capacity on the continuous review inventory policy, in which the order quantity, reorder point and lead-time are decision variables. Two models are considered: the normal lead-time demand and lead-time demand is distributed free. For both cases, after formulating the general model, some properties of the optimal ordering policy have been developed. Particularly, we have shown that the expected annual total cost is a unimodal function and quasi-convex in the order quantity. When the variable capacity distribution is exponential, we develop effective procedures for finding the optimal solutions. Furthermore, the effects of parameters are also performed.     

Managing stochastic demand in an Inventory Routing Problem with transportation procurement

We study an Inventory Routing Problem in which the supplier has a limited production capacity and the stochastic demand of the retailers is satisfied with procurement of transportation services. The aim is to minimize the total expected cost over a planning horizon, given by the sum of the inventory cost at the supplier, the inventory cost at the retailers, the penalty cost for stock-out at the retailers and the transportation cost. First, we show that a policy based just on the average demand can have a total expected cost infinitely worse than the one obtained by taking into account the overall probability distribution of the demand in the decision process. Therefore, we introduce a stochastic dynamic programming formulation of the problem that allows us to find an optimal policy in small size instances. Finally, we design and implement a matheuristic approach, integrating a rollout algorithm and an optimal solution of mixed-integer linear programming models, which is able to solve realistic size problem instances. Computational results allow us to provide managerial insights concerning the management of stochastic demand.     

提前期、构建成本和短缺量拖后率均可控的EOQ模型

传统库存模型通常将提前期和构建成本视为不可控制。事实上可以通过追加投资缩短提前期和降低构建成本。缺货期间,为减少订单丢失量和补偿顾客的损失,供应商会给予一定的价格折扣。现实库存系统中,容易得到需求的期望值和标准差,但较难得到其分布规律。基于此,考虑短缺量拖后率与价格折扣和缺货期间库存水平相关,提出了一种需求为任意分布且提前期和构建成本均可控的EOQ模型,证明了模型存在唯一最优解,给出了一种寻优算法。数值仿真分析表明,一般情况下,压缩提前期和降低构建成本能降低订购批量和安全库存,降低库存总成本;短缺量拖后系数和缺货概率对库存总成本影响较大,企业应尽量降低缺货概率,尤其在短缺量拖后系数较小时。     

Multi-item EOQ inventory model with varying holding cost under two restrictions: A geometric programming approach

In this paper we provide a simple method to determine the inventory policy of multiple items having varying holding cost using a geometric programming approach. The varying holding cost is considered to be a continuous function of the order quantity. The EOQ inventory model with constant holding cost and the classical EOQ inventory model without constraints are derived.     

Constrained production lot-size model with trade-credit policy: 'A comparison geometric programming approach via Lagrange'

In this paper our main objective is to investigate a deterministic inventory production lot-size model with a permissible delay in payment under a restriction. We analyse our deterministic inventory model under a restriction which will be assumed as the average inventory level. In fact we use in our analysis two approaches: the geometric programming approach; and the Lagrange method. Then a comparison between these two approaches is performed, which is our aim. Finally we deduce some previously published works of other researchers as special cases.     

A simple approach to an integrated single-vendor single-buyer inventory system with shortage

In this article, a simple approach with two basic inequalities (Cauchy–Schwarz inequality and arithmetic–geometric mean inequality) is used to solve the integrated single-vendor single-buyer inventory problem developed by Wu and Ouyang (Wu, K.-S. and Ouyang, L.-Y., 2003. An integrated single-vendor single-buyer inventory system with shortage derived algebraically. Production Planning & Control, 14 (6), 555–561). Without the method of completing perfect square, the proposed approach yields the global minimum of the integrated total cost per year more easily than the algebraic approach used by Wu and Ouyang (2003 Wu, K-S and Ouyang, L-Y. 2003. An integrated single-vendor single-buyer inventory system with shortage derived algebraically. Production Planning & Control, 14(6): 555–561. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). In addition, for people without the background of calculus, it is more useful to determine the buyer's economic order quantity and the vendor's optimal number of deliveries.     

需求替代情形下反应能力的价值分析

本文通过对竞争报童模型加以拓展以研究需求替代情形下企业运用反应能力产生的价值。文中考虑了两种不同的需求结构:第一种中企业总需求是竞争双方库存量的分段线性函数,第二种中企业总需求的均值是双方库存水平任意形式的函数。根据需求结构的不同,建立了不同的库存竞争模型并提出了相应的均衡库存策略。基于这些均衡结论,进一步探讨了反应能力的价值。分析表明运用反应能力能在降低企业库存水平的同时提高顾客服务水平。此外,在不同的需求结构下,运用反应能力产生的价值均随可用反应能力以及缺货惩罚成本递增,而随单位反应能力的使用成本递减。