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.     

两阶段闭环供应链的新产品和再制造产品最优定价模型

以一个制造商和一个零售商组成的两阶段闭环供应链为研究对象,通过考虑废旧产品的回收、再制造、再销售以及新产品和再制造产品竞争等因素,建立集中供应链系统和分散供应链系统的数学模型,研究新产品和再制造产品的最优定价策略.研究结果表明当新产品的制造成本和再制造产品的制造成本满足一定条件时,决策者为了实现利润最大化才进行再制造活动.最后通过算例验证了上述结论,并进一步分析了回收率和替代系数对供应链总利润及各成员利润的影响.     

"一带一路"背景下中国企业跨国 再制造决策研究

以"一带一路"倡议为背景,考虑了出口国原始设备制造商(OEM)自行生产新产品和再制造品、OEM生产新产品并授权进口国第三方制造商(TPR)生产再制造品两种跨国再制造模式,对比分析了两种模式下,再制造品价格、数量、决策主体利润等变量值的变化.结果表明:TPR生产的再制造品数量主要基于进口国消费者对其的认可程度;出于再制造生产过程更环保的角度考虑,政府会基于产品节能程度对产品市场需求的影响系数的大小选择OEM或TPR再制造;在不同的产品节能程度对产品市场需求的影响系数和投入的节能成本系数影响下,OEM和TPR对新产品和再制造品的价格、数量、利润等变量有不同的决策偏好.     

基于动态定价的再制造商主导的多周期多目标产品回收网络设计

假设回收商和制造/再制造商为独立理性的决策者,并共同构建回收网络,且制造/再制造商在两者的博弈中处于主导地位。另考虑废旧品回收率是回收价格的线性函数,结合回收定价与回收网络设计,建立基于动态定价的回收网络双层规划模型,上层规划为制造/再制造商进行再制造工厂的选址,确定回收补贴价格,下层规划为回收商进行回收中心的选址,确定废旧品的回收价格。通过建立模型求解算法,并给出算例论证模型的有效性。     

两阶段再制造企业的产品定价研究

二手产品的回收再处理是众多制造商和再制造商不得不面对的问题.企业根据实际情况,考虑到顾客对再制造产品的认知差异,一般都是先翻新产品然后再升级再制造产品,因此,顾客对再制造产品的接受程度影响着再制造企业的定价决策,针对该问题构建了一个两阶段模型,其中第一阶段再制造企业将回收的产品进行简单翻新并投放市场;第二阶段,则会将产品拆卸加工再升级.以两阶段的价格作为决策变量分析再制造企业的最优生产策略.通过仿真得出结论,为再制造企业的生产决策提供一些依据.     

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.     

考虑政府约束的再制造闭环供应链差别定价博弈模型

本文考虑政府对废弃产品回收的奖惩约束措施,针对一类由制造商、零售商构成的再制造闭环供应链系统,基于博弈论方法研究了新产品和再制造品存在定价差别时集中决策和分散决策模式下的定价策略,得出了闭环供应链成员的最优定价策略和利润,并分析了政府约束措施对闭环供应链运作的影响。研究表明:集中决策下供应链效率高于Stackelberg博弈分散决策,为此设计了一个收益共享协调定价契约实现了闭环供应链的协调,进而分析了政府回收约束情况下再制造过程利润超过制造过程的再制造优先条件。算例分析验证了定价策略及协调机制的有效性。     

回收量不确定下考虑技术授权的闭环供应链产品定价研究

越来越多的企业开始采取再制造的运作模式以缓解资源浪费和环境危机。原始设备制造商(OEM)为专注于新产品制造,可通过技术授权的方式委托第三方再制造商(TPR)进行再制造活动。本文研究了回收量不确定且OEM技术授权TPR进行再制造情形下闭环供应链的产品定价问题。研究发现:(1)当废旧品回收量在较小范围波动时,OEM和TPR若想获得不低于确定情形下的利润需考虑企业风险规避程度的影响;(2)当废旧品回收量在较大范围波动时,OEM和零售商在分别制定产品批发价和零售价时需按废旧品回收量波动方向相反的方向进行;(3)在废旧品回收量波动情形下,OEM应优先选择与风险中性的TPR合作,再适当降低技术授权费用使得TPR有利可图,这样既有利于促进废旧品的回收,也益于双方合作关系的持续发展。     

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.     

考虑提供基础质保服务的供应链再制造定价策略研究

再制造产品对新产品需求存在互补与挤兑现象,商家为再制造产品提供基础质保服务刺激其需求的同时,也会使得新产品销量受阻.以一个制造商和一个零售商组成的两级供应链为对象,分别探讨制造商提供再制造与零售商提供再制造两种模式下的定价决策问题.研究结果表明:1)当再制造产品质量水平过低时,由于出售再制造产品需要承担高额的维修成本,因此为避免降低供应链总体收益不应该引入再制造策略;2)再制造产品故障率越高,为了对抗售后维修成本,商家制定的新产品与再制造产品间的均衡售价差异反而会越小;3)当再制造产品质量水平较低时,制造商(零售商)总能在另一方采用再制造策略的情形下受益.     

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.     

Supply planning models for a remanufacturer under just-in-time manufacturing environment with reverse logistics

We study a supply planning problem in a manufacturing system with two stages. The first stage is a remanufacturer that supplies two closely-related components to the second (manufacturing) stage, which uses each component as the basis for its respective product. The used products are recovered from the market by a third-party logistic provider through an established reverse logistics network. The remanufacturer may satisfy the manufacturer’s demand either by purchasing new components or by remanufacturing components recovered from the returned used products. The remanufacturer’s costs arise from product recovery, remanufacturing components, purchasing original components, holding inventories of recovered products and remanufactured components, production setups (at the first stage and at each component changeover), disposal of recovered products that are not remanufactured, and coordinating the supply modes. The objective is to develop optimal production plans for different production strategies. These strategies are differentiated by whether inventories of recovered products or remanufactured components are carried, and by whether the order in which retailers are served during the planning horizon may be resequenced. We devise production policies that minimize the total cost at the remanufacturer by specifying the quantity of components to be remanufactured, the quantity of new components to be purchased from suppliers, and the quantity of recovered used products that must be disposed. The effects of production capacity are also explored. A comprehensive computational study provides insights into this closed-loop supply chain for those strategies that are shown to be NP-hard.     

Dynamic pricing of remanufacturable products under demand substitution: a product life cycle model

We consider a manufacturer who sells both the new and remanufactured versions of a product over its life cycle. The manufacturer’s profit depends crucially on her ability to synchronize product returns with the sales of the remanufactured product. This gives rise to a challenging dynamic optimization problem where the size of both the market and the user pool are dynamic and their current values depend on the entire history. We provide an analytical characterization of the manufacturer’s optimal pricing, production, and inventory policies which lead to a practical threshold policy with a small optimality gap. In addition, our analysis offers a number of interesting insights. First, the timing of remanufacturing activity and its co-occurrence with new product manufacturing critically depends on remanufacturing cost benefits, attractiveness of the remanufactured product and product return rate. Second, there is a small upward jump in the price of the new product when remanufacturing is introduced. Third, the manufacturer keeps the new product longer on the market as the cost of remanufacturing decreases. Fourth, partially satisfying demand for the remanufactured item is never optimal, i.e., it is satisfied either fully or not at all. Finally, user pool and inventory of returned products are substitutes in ensuring the supply for future remanufacturing.     

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.     

Optimal acquisition and production policy in a hybrid manufacturing/remanufacturing system with core acquisition at different quality levels

We study the acquisition and production planning problem for a hybrid manufacturing/remanufacturing system with core acquisition at two (high and low) quality conditions. We model the problem as a stochastic dynamic programming, derive the optimal dynamic acquisition pricing and production policy, and analyze the influences of system parameters on the acquisition prices and production quantities. The production cost differences among remanufacturing high- and low-quality cores and manufacturing new products are found to be critical for the optimal production and acquisition pricing policy: the acquisition price of high-quality cores is increasing in manufacturing and remanufacturing cost differences, while the acquisition price of low-quality cores is decreasing in the remanufacturing cost difference between high- and low-quality cores and increasing in manufacturing and remanufacturing cost differences; the optimal remanufacturing/manufacturing policy follows a base-on-stock pattern, which is characterized by some crucial parameters dependent on these cost differences.     

A closed-loop logistics model for remanufacturing

Recoverable product environments are becoming an increasingly important segment of the overall push in industry towards environmentally conscious manufacturing. Integral to the recoverable product environment is the recoverable manufacturing system that focuses on recovering the product and extending its life through remanufacture or repair. Remanufacturing provides the customer with an opportunity to acquire a product that meets the original product standards at a lower price than a new product. The flow of materials and products in this environment occurs both from the customer to the remanufacturer (reverse flow), and from the remanufacturer to the customer (forward flow). Since most of the products and materials may be conserved, essentially this forms a closed-loop logistics system. We present a 0–1 mixed integer programming model that simultaneously solves for the location of remanufacturing/distribution facilities, the transshipment, production, and stocking of the optimal quantities of remanufactured products and cores. We also discuss the managerial uses of the model for logistics decision-making.     

Competition for cores in remanufacturing

We study competition between an original equipment manufacturer (OEM) and an independently operating remanufacturer (IO). Different from the existing literature, the OEM and IO compete not only for selling their products but also for collecting returned products (cores) through their acquisition prices. We consider a two-period model with manufacturing by the OEM in the first period, and manufacturing as well as remanufacturing in the second period. We find the optimal policies for both players by establishing a Nash equilibrium in the second period, and then determine the optimal manufacturing decision for the OEM in the first period. This leads to a number of managerial insights. One interesting result is that the acquisition price of the OEM only depends on its own cost structure, and not on the acquisition price of the IO. Further insights are obtained from a numerical investigation. We find that when the cost benefits of remanufacturing diminishes and the IO has more chance to collect the available cores, the OEM manufactures less in the first period as the market in the second period gets larger to protect its market share. Finally, we consider the case where consumers have lower willingness to pay for the remanufactured products and find that in that case remanufacturing becomes less profitable overall.     

Joint control of production,remanufacturing, and disposal activities in a hybrid manufacturing–remanufacturing system

To generate insights into how production of new items and remanufacturing and disposal of returned products can be effectively coordinated, we develop a model of a hybrid manufacturing–remanufacturing system. Formulating the model as a Markov decision process, we investigate the structure of the optimal policy that jointly controls production, remanufacturing, and disposal decisions. Considering the average profit maximization criterion, we show that the joint optimal policy can be characterized by three monotone switching curves. Moreover, we show that there exist serviceable (i.e., as-new) and remanufacturing (i.e., returned) inventory thresholds beyond which production cannot be optimal but disposal is always optimal. We also identify conditions under which idling and disposal actions are always optimal when the system is empty. Using numerical comparisons between models with and without remanufacturing and disposal options, we generate insights into the benefit of utilizing these options. To effectively coordinate production, remanufacturing, and disposal activities, we propose a simple, implementable, and yet effective heuristic policy. Our extensive numerical results suggest that the proposed heuristic can greatly help firms to effectively coordinate their production, remanufacturing, and disposal activities and thereby reduce their operational costs.     

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.