回收率依赖回收产品质量的再制造EOQ模型

研究回收率依赖回收产品质量情况下制造/再制造混合系统的EOQ模型.该模型假设顾客的需求可通过新产品的制造和回收产品的再制造两种方式满足,且这两种产品无质量差异;需求率是确定的、连续的;总成本包括制造和再制造的固定启动成本,可销售产品和回收品的库存成本,以及缺货成本.当假设缺货成本无限大时给出不允许缺货情况下的模型.给出算例验证模型的有效性.     

需求依赖于服务水平的易变质品库存策略研究

本文研究需求依赖于上一周期服务水平、缺货时订单部分损失的两周期易变质品库存问题。分别考虑一次订货和多次订货两种情况,以平均利润最大化为目标构建库存模型,证明了模型解的存在性和唯一性,得到了最优库存服务水平和最优补货策略。最后,通过算例给出两个模型的应用,对重要参数进行了灵敏度分析,并且将两种模型的结果进行了对比分析。结果表明:订单损失率的增加会提高服务水平,但会使得利润降低;顾客期望服务水平的提高会降低第一阶段的服务水平,同时使利润减少;单位库存持有成本或变质率的增加会降低服务水平和平均利润。通常情况,企业通过多次订货能获得更大的利润,而只有当库存持有成本极小时,一次订购才能够获得更大的利润。同时,结果也表明:服务水平对库存策略有较大的影响,因此在进行库存决策时考虑服务水平具有重要的作用。     

基于承诺交货期的两阶通用件库存模型

在一个两阶段生产系统中,针对第二阶段应用单通用件的情况,引入承诺交货期因素,分别建立了第一阶段无通用件、单通用件、双通用件库存模型,考查了承诺交货期对通用件库存模型总成本的影响,分析了三类模型相应的最优库存水平。通过算例,说明了在一个第二阶段采用单通用件的两阶段生产系统中,当通用件与非通用件的单位采购成本相同时,并非第一阶段使用越多的通用件,总成本就越低。     

生产系统的检修时间间隔及关键备件采购的联合优化研究

研究了检修间隔时间与零备件库存采购的联合优化问题.利用带有吸收状态的连续时间马尔科夫链表示有m个生产状态以及一个损坏状态的生产系统,这个系统的再生点是生产系统的维修或检修完成的时刻点.利用更新过程报酬定理给出单位时间维修成本,利用概率分析技术给出备件库存的单位时间成本,进而得到整个生产系统的单位时间的总成本.最后,通过...     

需求率依赖于库存水平的离散性库存费的库存模型

传统的库存控制模型都视需求率为固定不变的,放松了这个假定,通过考虑库存费为存储时间的阶梯函数的情形:(1)全单位库存费用,(2)增量库存费用,并且在需求率依赖于库存水平,当库存水平下降到一定程度时,需求率变为常数的形式下,把变化的订购费引入,发展了两个离散性库存费的变质物品的库存控制模型。在模型中允许周期末库存水平不为零,并且提出了最优解的算法。     

多行程车辆路径问题和配送中心定位问题的研究

为了同时解决多行程车辆路径问题和配送中心的定位问题,首先开发了一个以最小化总成本为目标的数学模型,其中总成本包括运输成本和车辆启动成本.然后设计了一个启发式算法解决这个问题,包括三个阶段:第一阶段是找到初始定位并进行路线安排,第二阶段采用模拟退火(SA)的逻辑和交换算法来获得更好的路线,最后阶段是改善由模拟退火算法中当前温度控制的位置.通过标准样例进行的实验结果表明,该算法可以更好地获得一个配送中心定位和有效的相关路线安排.最后,数值实验指出:1)选择不同类型行程的配送方式取决于每辆车的启动成本和单位距离的运输成本;2)使用大容量车辆可以更好地减少运输距离.3)增加服务时间可以有效地减少所需车辆的数量,这三个结果对于多行程车辆路径问题和配送中心的定位问题的管理决策都具有一定的实用价值.     

不确定需求下再制造系统回收、生产与定价策略研究

以单一制造商为研究对象,在需求不确定且回收量依赖于需求量的环境下,构建基于期望利润最大化的数学模型,给出最优的回收率、新品和再制造品生产量及销售价格,并通过解析和数值仿真分析了市场规模、单位节约成本、回收成本的规模参数和需求不确定性对最优策略的影响.结果表明:市场规模增大,销售价格、回收率、生产量和再制造量都随之增大,而新品生产量先增大后减小;单位节约成本越大,回收成本的规模参数越小时,进行再制造就越有利;需求不确定性增加时,进行再制造更有利,可以降低由需求不确定性所造成的损失.     

考虑缺货的闭环供应链选址-库存-路径集成优化

再制造是企业实现环境友好、提升经济效益的重要策略之一;再制造的发展推动了新商业模式的出现,即产品服务系统;高效的再制造物流网络对于成功实施再制造十分重要。本文研究了基于产品服务系统下的再制造物流网络集成优化问题,即闭环供应链的选址-库存-路径的集成优化决策问题,且在库存策略中允许库存出现缺货的情况;论文基于产品服务系统模式构建了混合非线性规划模型来最小化生产、选址、配送、库存以及缺货成本,并采用了改进的禁忌搜索算法进行求解。通过与传统禁忌搜索算法的计算结果进行对比,表明本文中的算法能在可接受的时间内得到较优解。通过算例的敏感性分析得出,企业所服务的顾客如果接受再制造产品,提高回收率可以节约成本;在回收率一定时,客户在缺货情形下的制造和再制造批量比不允许缺货时要大,企业总成本比不允许缺货时要小。     

考虑RFID应用的资金约束供应链订购决策研究

RFID技术的应用在有效降低商品库存损耗率的同时,也增加了供应链企业的运营成本,尤其是具有资金压力的供应链中小企业。在零售商具有资金约束的二级供应链下分析RFID技术的应用对资金约束供应链绩效的影响,通过构建贸易信贷下基于批发价合同的Stackelberg博弈模型,对比采用RFID前后资金约束供应链成员的均衡决策及期望收益,探讨了该供应链采用RFID的必要条件。结果显示当RFID标签成本低于某个阈值,或RFID库存损耗恢复率高于某个阈值时,供应链成员会选择采用RFID。此外,当RFID单位标签成本或零售商标签成本分摊系数较低,或RFID库存损耗恢复率较高时,制造商会提供比不采用RFID时更高的批发价;在采用RFID的条件下,零售商订购数量低于不采用RFID时的数量。通过设计收益分享契约实现了采用RFID时资金约束供应链的协调。     

基于可控提前期和可变押后订单比例的库存问题研究

针对可控提前期领域现有研究中存在的不足,提出了同时考虑可控提前期和缺货对押后订单比例影响的连续盘点库存管理问题。在市场需求服从正态分布条件下建立年总成本表达式,并同时决策订货量、订货点和提前期使年总成本最小。实例计算表明我们的库存管理方法可以减少总成本,提高顾客服务水平和使库存管理更加平稳。     

On the Effect of Product Variety in Production–Inventory Systems

In this paper, we examine the effect of product variety on inventory costs in a production–inventory system with finite capacity where products are made to stock and share the same manufacturing facility. The facility incurs a setup time whenever it switches from producing one product type to another. The production facility has a finite production rate and stochastic production times. In order to mitigate the effect of setups, products are produced in batches. In contrast to inventory systems with exogenous lead times, we show that inventory costs increase almost linearly in the number of products. More importantly, we show that the rate of increase is sensitive to system parameters including demand and process variability, demand and capacity levels, and setup times. The effect of these parameters can be counterintuitive. For example, we show that the relative increase in cost due to higher product variety is decreasing in demand and process variability. We also show that it is decreasing in expected production time. On the other hand, we find that the relative cost is increasing in expected setup time, setup time variability and aggregate demand rate. Furthermore, we show that the effect of product variety on optimal base stock levels is not monotonic. We use the model to draw several managerial insights regarding the value of variety-reducing strategies such as product consolidation and delayed differentiation.     

An elaborative unit cost structure-based fuzzy economic production quantity model

The purpose of this paper is to investigate and propose a fuzzy extended economic production quantity model based on an elaboratively modeled unit cost structure. This unit cost structure consists of the various lot-size correlative components such as on-line setups, off-line setups, initial production defectives, direct material, labor, and depreciation in addition to lot-size non-correlative items. Thus, the unit cost is correlatively modeled to the production quantity. Therefore, the modeling or the annual total cost function developed consists of not only annual inventory and setup costs but also production cost. Moreover, via the concept of fuzzy blurred optimal argument and the vertex method of the α-cut fuzzy arithmetic (or fuzzy interval analysis), two solution approaches are proposed: (1) a fuzzy EPQ and (2) a compromised crisp EPQ in the fuzzy sense. An optimization procedure, which can simultaneously determine the α-cut-vertex combination of fuzzy parameters and the optimizing decision variable value, is also proposed. The sensitivity model for the fuzzy total cost and thus EPQ to the various cost factors is provided. Finally, a numerical example with the original data collected from a firm demonstrates the usefulness of the new model.     

Optimal production control of a dynamic two-product manufacturing system with setup costs and setup times

This paper deals with the optimal control of a one-machine two-product manufacturing system with setup changes, operating in a continuous time dynamic environment. The system is deterministic. When production is switched from one product to the other, a known constant setup time and a setup cost are incurred. Each product has specified constant processing time and constant demand rate, as well as an infinite supply of raw material. The problem is formulated as a feedback control problem. The objective is to minimize the total backlog, inventory and setup costs incurred over a finite horizon. The optimal solution provides the optimal production rate and setup switching epochs as a function of the state of the system (backlog and inventory levels). For the steady state, the optimal cyclic schedule is determined. To solve the transient case, the system's state space is partitioned into mutually exclusive regions such that with each region, the optimal control policy is determined analytically.     

On a production-inventory system of deteriorating items subject to random machine breakdowns with a fixed repair time

This paper considers the impact of random machine breakdowns on the classical Economic Production Quantity (EPQ) model for a product subject to exponential decay and under a no-resumption (NR) inventory control policy. A product is manufactured in batches on a machine that is subject to random breakdowns in order to meet a constant demand over an infinite planning horizon. The product is assumed to have a significant rate of deterioration and time to deterioration is described by an exponential distribution. Also, the time-to-breakdown is a random variable following an exponential distribution. Under the NR policy, when a breakdown occurs during a production run, the run is immediately aborted. A new run will not be started until all available inventories are depleted. Corrective maintenance of the production system is carried out immediately after a breakdown and it takes a fixed period of time to complete such an activity. The objective is to determine the optimal production uptime that minimizes the expected total cost per unit time consisting of setup, corrective maintenance, inventory carrying, deterioration, and lost sales costs. A near optimal production uptime is derived under conditions of continuous review, deterministic demand, and no shortages.     

Control policies for single-stage production systems with perishable inventory and customer impatience

We consider problems of inventory and admission control for make-to-stock production systems with perishable inventory and impatient customers. Customers may balk upon arrival (refuse to place orders) and renege while waiting (withdraw delayed orders) during stockouts. Item lifetimes and customer patience times are random variables with general distributions. Processing, setup, and customer inter-arrival times are however assumed to be exponential random variables. In particular, the paper studies two models. In the first model, the system suspends its production when its stock reaches a safety level and can resume later without incurring any setup delay or cost. In the second model, the system incurs setup delays and setup costs; during stockouts, all arriving customers are informed about anticipated delays and either balk or place their orders but cannot withdraw them later. Using results from the queueing literature, we derive expressions for the system steady-state probabilities and performance measures, such as profit from sales and costs of inventory, setups, and delays in filling customer orders. We use these expressions to find optimal inventory and admission policies, and investigate the impact of product lifetimes and customer patience times on system performance.     

An optimal (Q,r) policy for a multipart assembly system under stochastic part procurement lead times

We consider an EOQ-type model for a simple production system, where a number of parts are acquired to produce a single product and the part procurement lead times are random. Assembly is instantaneous and takes place intermittently in batches but cannot start until all the parts are available. The problem is to simultaneously determine when to order each part and what lot size to produce, namely to determine the reorder point for each part and the assembly lot size, so that the average total cost per unit time, composed of the setup cost, inventory holding costs for the parts and the assembled product, and the shortage cost for the assembled product, is minimized. We then develop a tailormade solution method for this problem to obtain a global optimal solution by taking advantage of the structure of the problem formulation, where the nonlinear programming problem is decomposed into a family of subproblems parametrized by the average assembly delay time. Numerical experiments are then conducted for the case of twopart problems, and some interesting observations are made.     

Optimal policy for brownian inventory models with general convex inventory cost

We study an inventory system in which products are ordered from outside to meet demands, and the cumulative demand is governed by a Brownian motion. Excessive demand is backlogged. We suppose that the shortage and holding costs associated with the inventory are given by a general convex function. The product ordering from outside incurs a linear ordering cost and a setup fee. There is a constant leadtime when placing an order. The optimal policy is established so as to minimize the discounted cost including the inventory cost and ordering cost.     

Integrated production-inventory models with imperfect production processes and a limited capacity for raw materials

This paper deals with inventory models that unify the decisions for raw materials and the finished product for a single product manufacturing system. The product is manufactured in batches and raw materials are jointly replenished from outside suppliers. The system is assumed to deteriorate during the production process. As a result, some proportion of nonconforming items is produced. The objective is to minimize the total variable cost for the system. A solution procedure is developed to find a near optimal solution for the basic model. The analysis for the basic model is extended to cases where the proportion of defective items is not constant or the defective rate is a function of production setup cost.     

On an (<Emphasis Type="Italic">s,Q</Emphasis>) Production Policy for an Integrated Inventory Model for a Single Product with Linearly Increasing Demand

We analyse an (s, Q) production policy for an inventory system consisting of a single finished product and the raw materials used for manufacturing it, and where the demand rate of the product increases linearly with time. We formulate a mathematical programming model with the objective of minimizing total inventory cost per unit time. The problem of grouping raw materials optimally so that common replenishment periods may be used is considered. Solution procedures are developed, and numerical examples are presented.