回收率依赖价格的再制造EPQ模型研究

研究了考虑回收率依赖于回收品价格,并带有废弃处理的制造和再制造混合系统的(1,R)和(M,1)EPQ模型.在模型中,采用新产品的制造和回收产品的再制造两种方式来满足客户的需要,回收产品部分用于再制造,其余作为废弃处理;总平均成本包括与回收产品、可销售产品有关的库存持有成本,与制造和再制造有关的生产成本和固定成本,与回收品及制造所需原材料的采购成本以及废弃处理成本.模型给出最优生产策略及总平均成本的表达式.算例验证了所建模型的计算方法,并分析了新引人决策变量p(回收产品单价占制造新产品所需原料价格的比例对总平均成本的变化率的影响.     

顾客搜索强度影响下短生命周期产品订货决策

根据短生命周期产品的特点,考虑与需求相关的顾客搜索强度,在假设溢出需求为顾客搜索强度函数的情况下,建立了考虑顾客搜索强度因素的斜坡型需求模型,分两种情形对模型最优解进行了存在性证明和求解.然后通过数值算例分析了主要参数变化对缺货时间、订货量、库存成本的影响,发现订货量与顾客搜索强度同方向变动,缺货时间与需求变化临界点出现先后的不同,缺货成本、持有成本和变质成本对库存总成本的影响不同.     

模糊环境下基于再制造闭环供应链的博弈问题研究

研究了模糊环境下基于再制造闭环供应链的博弈问题,通过考虑存在于回收过程,制造(再制造)过程及需求过程中的模糊不确定性,建立了三种不同的再制造闭环供应链博弈模型,给出了制造商和回收商(零售商)的最优均衡决策,分析了制造商和回收商(零售商)博弈能力对废旧产品的回收,制造(再制造)产品的销售及系统成员利润的影响.利用数值算例对所得结果和关键参数进行了分析.     

基于数量折扣合同和缺货损失的EOQ模型的改进

经济订购批量模型假定需求率、单位持有成本、订货成本为常数下得到总成本最低的订购批量,这些参数常数化的假设在现实中通常难以满足.假定需求和订货费为不确定的、库存成本包括年固定成本(与订货量无关)和年可变成本(与订货量有关),用三角模糊数表示年需求和订货费,通过引入数量折扣合同来量化单位产品进价,分别在不允许缺货和考虑缺货损失两种情况下得到最佳订货量.最后的算例表明了模型的合理性.     

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。     

再制造能力有限的多产品混合系统库存决策

为确定各产品的制造与再制造策略,对再制造能力有限的多产品混合系统进行研究.在系统中,对多种产品进行制造和再制造.每种产品在顾客使用后都会以恒定速率返回,但因再制造能力有限,有些产品无法用于再制造而被处置.每种产品需求恒定且由服务性产品来满足,服务性产品由制造品和再制造品组成,不允许缺货.在一次制造准备和至少一次再制造准备策略下构建了库存决策模型,利用拉格朗日乘数法和贪婪算法分别确定了各产品的再制造顺序和再制造比率.并当再制造比率一定时,给出了再制造准备次数为正整数时各产品制造与再制造策略的求解程序,得到了各产品制造和再制造批量、再制造准备次数等求解公式.最后,应用算例对模型及求解方法进行了验证.     

考虑返回补偿策略的制造与再制造的最优决策

作为减少成本的一种有效方式,近年来,再制造获得了企业越来越多的关注.对于再制造企业,如何有效地返回产品是一个基本的问题,为此,考虑了一个返回补偿策略,即企业支付给愿意返回产品的消费者一个价格补偿.在这个策略下,回收数量是随机需求的一个比例.研究了一个两周期的库存系统,企业需要在每周期初决策新材料的采购数量以及分配给制造和再制造方式的生产数量.通过建立一个三级随机动态规划模型,给出了制造和再制造混合系统对于已实现需求的最优生产策略,同时证明了每个周期的目标函数对于库存补充数量是凸的,进而证明基本的库存策略仍然是最优的.最后从管理者的角度进行了数值分析.     

基于碳交易的闭环供应链碳减排与定价策略研究

在消费者对低碳产品存在偏好的碳交易市场中,研究两级闭环供应链中的减排与定价决策问题.对于制造商负责回收模式下的回收再制造过程,采用指数分布来刻画废旧产品质量水平的不确定性.假设新产品和再制造品存在竞争关系,建立制造商和零售商间的Stackelberg博弈模型,给出制造商确定减排投资和回收参考价格以及零售商决定两种产品的差别定价策略,通过算例分析回收产品的残值和碳交易价格对最优策略和供应链成员利润的影响.研究表明,为了获得利润最大,当碳交易的市场价格升高时,制造商应加大减排投资,且零售商应采取提高产品零售价的策略.     

基于回收质量差异化的回收努力程度决策与额外再制造率投资策略研究

构建一个由制造商和第三方回收商组成的再制造闭环供应链,制造商是领导者,决定是否投资额外再制造率,第三方回收商作为追随者付出回收努力程度及其成本从消费者手里回收废旧产品.在制造商不投资情境下,废旧产品的回收质量呈现差异化且基准再制造率与回收质量成正比,而在投资情境下额外再制造率由制造商制定并能够进一步降低再制造成本.在此基础上,研究制造商投资额外再制造率的动机和相关参数的影响机理.研究发现:1)消费者无偿参与回收的初始回收量越多,废旧产品的回收质量越高,第三方回收商越受益;2)制造商选择不投资再制造率的动机是废旧产品的回收质量高于一定阈值;3)当基准再制造率较低或内生后带来的单位产品节省较高且投资额外再制造成本不是很高时,制造商投资额外再制造率是有利可图的.     

考虑专利许可的制造商与再制造商竞争策略

研究了在专利完善市场受专利保护的原制造商面对再制造商竞争所采取得两种策略:无许可再制造与许可再制造。在再制造成本差异及消费者异质的情况下,分别建立了无回收数量限制的单周期模型和受回收数量限制的两周期模型,利用博弈理论求解原制造商和再制造商竞争情况下的最优决策。通过比较分析和数值仿真,讨论了不同参数对新产品和再制造品定价策略及双方利润的影响,并给出了相关结论。结果表明,原制造商倾向于采用许可再制造策略,这是在于原制造商可以通过收取专利许可费来分享再制造所带来的收益;而对再制造商而言,只有许可再制造所带来的节省成本足够高时,才有意愿接受原制造商的专利技术支持。     

Lot sizing for a single product recovery system with variable setup numbers

Inventory systems for joint remanufacturing and manufacturing have recently received considerable attention. In such systems, used products are collected from customers and are kept at the recoverable inventory warehouse for future remanufacturing. In this paper a production–remanufacturing inventory system is considered, where the demand can be satisfied by production and remanufacturing. The cost structure consists of the EOQ-type setup costs, holding costs and shortage costs. The model with no shortage case in serviceable inventory is first studied. The serviceable inventory shortage case is discussed next. Both models are considered for the case of variable setup numbers of equal sized batches for production and remanufacturing processes. For these two models sufficient conditions for the optimal type of policy, referring to the parameters of the models, are proposed.     

Four-level closed loop supply chain with remanufacturing

This paper addresses the coordination of order quantities in a four-level closed-loop supply chain (CLSC) with remanufacturing. The levels are multiple buyers and tier-1 and tier-2 suppliers, and a manufacturer. The reverse channel consists of an inspection and disassembly center and a remanufacturing center. Customer demand is met from either newly manufactured items, remanufacturing used items collected from customers for recovery, or from both. Mathematical models are developed to find the production (manufacturing and remanufacturing) and inventory policies that minimize the CLSC total cost. One of the models considers emissions from production and transportation and accounts for energy usage. The results showed that higher collection rates of used items reduce the supply chain costs and improves its environmental performance. A mixed strategy of manufacturing and remanufacturing was found to be best for the chain.     

Heuristics with guaranteed performance bounds for a manufacturing system with product recovery

We consider a manufacturing system with product recovery. The system manufactures a new product as well as remanufactures the product from old, returned items. The items remanufactured with the returned products are as good as new and satisfy the same demand as the new item. The demand rate for the new item and the return rate for the old item are deterministic and constant. The relevant costs are the holding costs for the new item and the returned item, and the fixed setup costs for both manufacturing and remanufacturing. The objective is to determine the lot sizes and production schedule for manufacturing and remanufacturing so as to minimize the long-run average cost per unit time. We first develop a lower bound among all classes of policies for the problem. We then show that the optimal integer ratio policy for the problem obtains a solution whose cost is at most 1.5% more than the lower bound.     

Optimal production inventory policy for defective items with fuzzy time period

In this paper, an optimal production inventory model with fuzzy time period and fuzzy inventory costs for defective items is formulated and solved under fuzzy space constraint. Here, the rate of production is assumed to be a function of time and considered as a control variable. Also the demand is linearly stock dependent. The defective rate is taken as random, the inventory holding cost and production cost are imprecise. The fuzzy parameters are converted to crisp ones using credibility measure theory. The different items have the different imprecise time periods and the minimization of cost for each item leads to a multi-objective optimization problem. The model is under the single management house and desired inventory level and product cost for each item are prescribed. The multi-objective problem is reduced to a single objective problem using Global Criteria Method (GCM) and solved with the help of Fuzzy Riemann Integral (FRI) method, Kuhn–Tucker condition and Generalised Reduced Gradient (GRG) technique. In optimum results including production functions and corresponding optimum costs for the different models are obtained and then are presented in tabular forms.     

A production planning model for an unreliable production facility: Case of finite horizon and single demand

We study a two-level inventory system that is subject to failures and repairs. The objective is to minimize the expected total cost so as to determine the production plan for a single quantity demand. The expected total cost consists of the inventory carrying costs for finished and unfinished items, the backlog cost for not meeting the demand due-date, and the planning costs associated with the ordering schedule of unfinished items. The production plan consists of the optimal number of lot sizes, the optimal size for each lot, the optimal ordering schedule for unfinished items, and the optimal due-date to be assigned to the demand. To gain insight, we solve special cases and use their results to device an efficient solution approach for the main model. The models are solved to optimality and the solution is either obtained in closed form or through very efficient algorithms.     

An inventory model for ameliorating/deteriorating items with trapezoidal demand and complete backlogging under inflation and time discounting

Recently, numerous inventory models were developed for ameliorating items (say, fish, ducklings, chicken, etc.) considering the constant demand rate. However, such types of problems are not useful in the real market. The demand rate of ameliorating items is fluctuates in their life‐period. The consumption and demand of ameliorating items are not generally steady. In a few seasons, the demand rate increases; ordinarily, it is static, and sometimes, it declines. With the outcome that their demand rate can be properly portrayed by a trapezoidal‐type. In the proposed model, an inventory model for ameliorating/deteriorating items are considered with inflationary condition and time discounting rate. Additionally, having shortages that is completely backlogged. The demand rate is taken as the continuous trapezoidal‐type function of time. The amelioration and deterioration rate are considered as Weibull distribution. To obtain the minimum cost, mathematical formulation of the proposed model with solution procedure is talked about. Numerical cases are given to be checked the optimal solution. Additionally, we have talked about the convexity of the proposed model through graphically. Conclusion with future worked are clarified appropriately. Copyright © 2016 John Wiley & Sons, Ltd.     

A note on the inventory models for deteriorating items with ramp type demand rate

In this research we study the inventory models for deteriorating items with ramp type demand rate. We first clearly point out some questionable results that appeared in (Mandal, B., Pal, A.K., 1998. Order level inventory system with ramp type demand rate for deteriorating items. Journal of Interdisciplinary Mathematics 1, 49–66 and Wu, K.S., Ouyang, L.Y., 2000. A replenishment policy for deteriorating items with ramp type demand rate (Short Communication). Proceedings of National Science Council ROC (A) 24, 279–286). And then resolve the similar problem by offering a rigorous and efficient method to derive the optimal solution. In addition, we also propose an extended inventory model with ramp type demand rate and its optimal feasible solution to amend the incompleteness in the previous work. Moreover, we also proposed a very good inventory replenishment policy for this kind of inventory model. We believe that our work will provide a solid foundation for the further study of this sort of important inventory models with ramp type demand rate.     

An Economic order quantity model for Items with Three-parameter Weibull distribution Deterioration,Ramp-type Demand and Shortages

In this paper, we develop an economic order quantity inventory model for items with three-parameter Weibull distribution deterioration and ramp-type demand. Shortages are allowed in the inventory system and are completely backlogged. The demand rate is deterministic and varies with time up to a certain point and eventually stabilized and becomes constant. The instantaneous rate of deterioration is an increasing function of time. We provide simple analytical tractable procedures for deriving the model and give numerical examples to illustrate the solution procedure. Our adoption of ramp-type demand reflects a real market demand for newly launched product.     

Towards a normative model for inventory cost management in a generalized ABC classification system

This paper establishes a general ABC inventory classification system as the foundation for a normative model of the maintenance cost structure and stock turnover characteristics of a large, multi-item inventory system with constant demand. For any specified number of inventory classes, the model allows expression of the overall system combined ordering and holding cost in terms of (i) the re-ordering frequencies for the items in each inventory class and (ii) the inventory class structure, that is, the proportion of the total system's items that are in each inventory class. The model yields a minimum total maintenance cost function, which reflects the effect of class structure on inventory maintenance costs and turnover. If the Pareto curve (a.k.a. Distribution-by-value function) for the inventory system can be expressed (or approximated) analytically, the model can also be used to determine an optimal class structure, as well as an appropriate number of inventory classes. A special case of the model produces a simply structured, class-based ordering policy for minimizing total inventory maintenance costs. Using real data, the cost characteristics of this policy are compared to those of a heuristic, commonly used by managers of multi-item inventory systems. This cost comparison, expressed graphically, underscores the need for normative modelling approaches to the problem of inventory cost management in large, multi-item systems.