基于碳足迹质量平衡的三级生产-库存协调模型

基于碳足迹质量平衡方程建立多级供应链生产-库存-碳足迹模型,研究多成员之间订货、生产与碳足迹协调问题。数值计算表明:执行最严厉或最宽松的碳排放控制政策,都会产生供应链成本与碳足迹背反,碳交易价格等于零时,供应链成本最低,而碳足迹最高。部分配额免费并结合碳交易,是控排早期可行的选择,价格机制对供应链决策调整更敏感。此外,协调效率曲线突出碳排放供应链协作价值,成本二次分配不仅可以降低运行成本,又能减少供应链碳足迹。     

考虑修复成本的逆向物流多级库存优化研究

通过对逆向物流多级库存的提法引入,提出了逆向物流多级库存总成本最小化问题．在对产品召回的条件下回收系统模型图简化的基础上,提出了考虑修复成本的逆向物流的多级库存成本优化模型,并用MATLAB编程计算实际算例,得出总成本的优化值．研究结果表明,考虑了修复成本的逆向物流多级库存成本优化更具实际应用意义．     

碳限额与交易机制下易变质产品供应链的生产库存控制策略研究北大核心CSSCI

针对易变质产品供应链,在低碳供应链中引入碳限额与交易机制,探讨考虑碳排放影响的生产库存控制策略,分析影响生产库存控制策略的因素,构建经济生产批量优化模型,通过算例讨论碳限额、碳价与变质率对供应链总成本、经济生产批量及总碳排放量的影响规律,并验证模型的有效性。     

碳限额与交易机制下易变质产品供应链的生产库存控制策略研究

针对易变质产品供应链,在低碳供应链中引入碳限额与交易机制,探讨考虑碳排放影响的生产库存控制策略,分析影响生产库存控制策略的因素,构建经济生产批量优化模型,通过算例讨论碳限额、碳价与变质率对供应链总成本、经济生产批量及总碳排放量的影响规律,并验证模型的有效性。     

基于优化模型求解方法的多级供应链生产-库存研究进展与趋势

多级生产-库存系统协调运营是供应链运作的重点问题,由现实问题抽象出优化模型,能通过各种求解方法得出运营结果。本文从解析法、数学规划法、启发式算法、其他运筹方法4个方面对多级生产-库存问题的研究文献进行归纳与分析,总结多级生产-库存问题求解方法的研究进展,发现未来研究新趋势。     

双渠道多级分销网络的预防性库存分拨机制与方法研究

企业通过增加库存量来应对不可延期交货带来的缺货损失的传统运作方式在电子商务催生了线上线下双渠道分销模式后变得捉襟见肘。在双渠道多级分销模式下，传统囤货式的运作模式因多层级、多渠道而产生高额库存成本，这恰恰削弱了双渠道销售的高利润优势。因此，拥有双渠道多级分销网络的企业如何平衡库存成本与缺货损失就成为了本文的研究重点。本文考虑了拥有线上线下双渠道销售的一个由中心仓、区域仓和门店节点构成的三级供应链库存系统，借鉴库存共享思想提出了“预防性库存分拨机制”，即节点内线上线下库存、同层级一对多双向预防性调拨、上下级间一对一单向预防性补货的运作机制，并利用目标级联法(analysis target cascading, ATC)依据预测时间窗内的需求预测结果构建预防性分拨模型。最后以国内某大型进口红酒贸易企业为基础对模型进行仿真和分析，结果表明所提出的预防性库存分拨机制能够有效降低库存成本，为双渠道供应链系统低成本高效率的运作提供了实现的手段。     

考虑价格折扣和运输柔性的库存运输优化研究

在考虑运输能力柔性和销售价格折扣的基础上,建立了零售商主导的分散优化模型、供应商主导的分散优化模型和库存运输联合优化模型,分析得出模型的性质。通过比较研究得出不同决策模式下最优策略和系统绩效的关系。研究表明,零售商主导的分散优化模型的库存成本小于运输库存联合优化模型的库存成本;零售商主导的分散优化模型的运输成本大于运输库存联合优化模型的运输成本;运输库存联合优化供应链的总成本小于零售商主导的供应链总成本。     

多级串行供应链的同步模式及库存优化研究

在Ciancimino和Cannella[1]提出的同步供应链概念模式上进行了数学建模,补充了库存更新的规则,提出同步供应链的单时段系统成本的核算方法,对同步模式与库存优化进行了结合研究。以系统成本为优化目标,获得供应链各级的最优安全库存因子,进行系统最优库存设置。通过算例模拟传统供应链和同步供应链的实际运作,利用通用的供应链评价指标对两种供应链模式进行比较分析,证实了结合库存优化的同步供应链模式的优越性。     

多供应链间库存互补系统动力学仿真模型

以两条或多条由生产商、批发商和零售商组成的三级供应链为研究对象,首先分别建立了两条供应链环境下零售商、批发商和生产商各级节点企业库存互补系统动力学仿真模型,然后把两链间库存互补问题扩展到多链间库存互补情况.研究表明,两条供应链各级节点企业问库存互补均能减少供应链系统的库存总量和总物流成本、减弱牛鞭效应、提高顾客服务水平...     

多级库存控制的连锁经营企业配送网络设计

研究了随机需求条件下连锁经营企业配送网络设计及其库存决策的联合优化问题.详细分析了基于POT(power of two)多级库存控制策略的连锁企业多级工作库存及订货成本,给出了门店及配送中心在满足给定服务水平条件下的安全库存成本.在综合考虑运输成本和配送中心选址成本的基础上,建立了以系统总成本最小为目标的配送系统总成本优化模型,并采用遗传算法求解该优化模型,在得到最优配送网络设计方案的同时,确定了配送中心订货周期及门店配送周期.通过算例验证了模型及算法的有效性,并分析了需求、运输距离和选址成本等因素的变化对系统总成本的影响,为连锁经营企业的物流配送网络设计及库存控制提供决策支持.     

Operational and environmental decisions for a two-stage supply chain under vendor managed consignment inventory partnership

Supply-chain-based organisations are nowadays facing intense pressure to abide to environmental regulatory requirements while they are striving to be responsive to customers’ needs at the least cost possible. As supply chain activities are among the top contributors to carbon emissions, several recent research works have investigated the impact of carbon regulation policies on economic and environmental supply chain performance. This paper presents integrated economic and environmental models for the one-vendor one-buyer supply chain problem under a vendor managed consignment inventory (VMCI) arrangement. Through the developed models, we study the impacts of two carbon reduction policies, namely carbon cap and carbon tax policies, on supply chain wide costs and carbon emissions. We first provide a much simpler and more compact formulation for the basic single-vendor single-buyer supply chain under VMCI agreement. We also present an environmental-based VMCI model where reduction of carbon footprint is considered as the only objective function. We then extend these two basic models to include each of the two carbon emissions reduction policies. We identify structural properties for the optimal solutions of the two hybrid economic and environmental models and propose algorithms to generate optimal solutions. The results of the computational experiments reveal that the implementation of carbon reduction policies, through carbon cap and carbon tax, may call for the adjustment of the vendor’s production and buyer’s delivery quantities to reduce carbon footprint without significantly increasing the operational costs.     

Optimal inventory policies when stockouts result from defective products

An implicit assumption underlying most inventory systems is that the lot ordered will not contain any defective, i.e., unsaleable items when delivered and so there will be no ‘shortages’ in the delivery in the sense that every unit of the product in the accepted lot is of perfect quality and therefore fully acceptable to the customers. Such an assumption is not always tenable in view of the extensive use of acceptance sampling by business and industry in the quality control process. The presence of defective items in the traditional inventory models which foresee no such possibility would certainly disrupt the systems in use, and consequently entail higher operating cost on the inventory management. With an aim to broaden the base of applications, and to demonstrate the impacts of the possible presence of defective products upon the structure and the cost of certain inventory systems, this paper extends two inventory models to the case where the proportion of defective units in the accepted lot is a random variable with known probability distributions. Optimal solutions to the modified systems are developed and comparisons with the traditional models are also presented via numerical examples.     

Learning and screening errors in an EPQ inventory model for supply chains with stochastic lead time demands

This paper investigates the role of variable lead time, learning in production and screening errors in a vendor–buyer supply chain with defective items. The vendor–buyer supply chain is modelled for supplying a single item considering that the lots from vendor may contain some defective items. It is assumed that demand during lead time follows a normal distribution. Moreover, the production time at vendor’s facility is assumed to follow learning whereas buyer’s screening for defective items is prone to errors as well. Numerical examples are presented to illustrate the impact of different variables in the model. The analysis shows that delay in transportation lead time forces the buyer to carry more inventories to avoid shortages. Further, Type I error has a major impact on this cost. It was found that learning in production keeps on reducing the total cost of the supply chain up to a threshold.     

A green vendor-managed inventory analysis in supply chains under carbon emissions trading mechanism

One of the most important strategies for reducing carbon emissions is to optimize firms’ operation decisions in business practices. This paper proposes a green vendor-managed inventory (a green VMI) model with a supplier and a manufacturer under a carbon emissions trading mechanism. The proposed model integrates both environmental and economic goals under a carbon emissions constraint, and then the members’ optimal decisions are obtained. Comparing this model with the traditional VMI model, this paper finds that, in the green VMI model, whether the supplier should sell or buy carbon credit depends on the carbon cap. Further, the impacts of the carbon cap and the carbon emissions factors on the optimal decisions, the carbon emissions, and the total costs in the supply chain are examined analytically. Finally, numerical experiments are performed to verify the theoretical results. It is shown that, after introducing the carbon trading mechanism, the VMI model could increase the total cost of the supply chain under some specified set of parameters.     

Uncertain supply chain network design considering carbon footprint and social factors using two-stage approach

Sustainable development has become one of the leading global issues over the period of time. Currently, implementation of sustainability in supply chain has been continuously in center of attention due to introducing stringent legislations regarding environmental pollution by various governments and increasing stakeholders’ concerns toward social injustice. Unfortunately, literature is still scarce on studies considering all three dimensions (economical, environmental and social) of sustainability for the supply chain. An effective supply chain network design (SCND) is very important to implement sustainability in supply chain. This study proposes an uncertain SCND model that minimizes the total supply chain-oriented cost and determines the opening of plants, warehouses and flow of materials across the supply chain network by considering various carbon emissions and social factors. In this study, a new AHP and fuzzy TOPSIS-based methodology is proposed to transform qualitative social factors into quantitative social index, which is subsequently used in chance-constrained SCND model with an aim at reducing negative social impact. Further, the carbon emission of supply chain is estimated by considering a composite emission that consists of raw material, production, transportation and handling emissions. In the model, a carbon emission cap is imposed on total supply chain to reduce the carbon footprint of supply chain. To solve the proposed model, a code is developed in AMPL software using a nonlinear solver SNOPT. The applicability of the proposed model is illustrated with a numerical example. The sensitivity analysis examines the effects of reducing carbon footprint cap, negative social impacts and varying probability on the total cost of the supply chain. It is observed that a stricter carbon cap over supply chain network leads to opening of more plants across the supply chain. In addition, carbon footprint of supply chain is found to be decreased in certain extent with the reduction in negative social impacts from suppliers. The carbon footprint of the supply chain is found to be reduced with increasing certainty of material supply from the suppliers. The total supply chain cost is observed to be augmented with increasing probability.     

具有缺陷品的双渠道供应链库存优化策略

为研究双渠道供应链库存优化问题，考虑由一个网络零售商和一个传统零售商构成的缺陷品双渠道供应链系统，允许不同渠道零售商之间采用横向转运策略协调库存水平，引入渠道间消费者购买转移，运用马尔科夫链来描述零售商的库存状态，建立以库存成本最小为目标的数学模型，并运用遗传算法进行求解。通过对允许转运和不允许转运2种方案的对比，得出在分销缺陷产品的双渠道供应链中，双渠道间采取转运策略可以降低最优库存量和总成本；随着购买转移概率的增加和产品缺陷率的增加，转运策略带来的系统绩效均不断降低。     

供应链管理环境下的单周期库存控制建模及优化

传统的库存控制理论已经不能够适应供应链管理的要求。在建立了供应链库存成本的组成模型的基础上对供应链管理中的单周期库存控制过程进行了深入的分析，建立了相应的数学模型，求出了最优解。     

碳限额及交易下低碳补贴和低碳宣传成本分摊的双渠道供应链联合减排策略

为了研究碳限额及交易下考虑低碳补贴和零售商低碳宣传的双渠道供应链联合减排策略问题,构建由一个制造商和一个零售商组成双渠道供应链,分别建立碳减排补贴与低碳宣传的双渠道供应链集中式决策模型以及无碳减排补贴且无低碳宣传成本分摊、有碳减排补贴但无低碳宣传成本分摊、碳减排补贴且低碳宣传成本分摊的双渠道供应链分散式决策模型,分析其最优决策,并指出政府碳减排补贴、碳减排成本和低碳宣传成本分摊能够实现双渠道供应链协调。研究结果表明,在碳限额及交易下,最优碳减排率、最优低碳宣传水平和双渠道供应链利润与政府补贴比例、低碳偏好对需求的影响系数、低碳宣传对线上消费者需求的影响系数、低碳宣传对线下消费者需求的影响系数都成正向变化关系;最优碳减排率、最优低碳宣传水平和双渠道供应链利润与低碳宣传成本系数、最优碳减排成本系数成反向变化关系;最优碳减排率与碳排放交易价格成正向变化关系,而最优低碳宣传水平、双渠道供应链利润与碳排放交易价格成反向变化关系。     

Collaborative model for a two-echelon supply chain with uncertain demand under carbon tax policy

Consideration of carbon policies while optimizing supply chain operations has become imperative as governments and regulatory bodies throughout the world have implemented different carbon policies to reduce emissions of greenhouse gasses, especially CO₂. “Carbon tax” is one of the major carbon policies, initiated by several governments to curtail emissions. In this study, we have considered this policy to optimize the total expected cost (TEC) of a two-echelon integrated supply chain with stochastic demand, where both backorders and lost sales are permitted. An unconstrained mixed integer non-linear programming (MINLP) problem is formulated and further solved to find the optimal production rate, order quantity, number of shipments and reorder point while minimizing the TEC. Emissions from all the major sources such as production, inventory and transportation have been taken into consideration. It is assumed that the emission from production is a function of production rate, and emission from transportation depends on payload and vehicle type. This study will help organizations to reduce cost and emissions, and regulatory bodies to decide proper tax rate on carbon emission.     

Impacts of collaborative investment and inspection policies on the integrated inventory model with defective items

For an imperfect production system, to reduce quality-related costs, a manager may consider investing capital in quality improvement. In general, the investment expense in reducing the defective rate of items is often paid by the vendor. On the other hand, the buyer may inspect the product quality as the order is received which implies it incurs an inspection cost. In a supply chain integrated system, to accomplish global optimisation, the vendor and buyer can agree to jointly invest capital to improve the imperfect production processes, and the buyer can remove the inspection programme as the defective rate reaches a certain low-level. Hence, this paper investigates the impacts of collaborative investment and inspection policies on an integrated inventory model with defective items. The objective of this study is to seek the optimal order quantity, shipping times from the vendor to the buyer per production run, and the defective rate that minimise the joint total cost per unit time. An algorithm is developed to find the optimal solution. Several numerical examples are presented to demonstrate the proposed model and solution procedure, and then several management insights are obtained from the numerical examples.