奖惩机制下闭环供应链的成本共担-利润共享契约

研究政府奖惩机制下闭环供应链的成本共担-利润共享契约,分别建立集中式决策情形和分散式决策情形下的奖惩机制下有无成本共担-利润共享契约的闭环供应链决策模型.研究表明:随着政府奖惩力度的提高,产品的零售价降低,回购价、回收率和回收商的利润均提高,但制造商的利润与目标回收率有关;随着回收商成本共担比例和分享利润比例的提高,零售价提高,但总小于无契约的情形,回收率降低,但总大于无契约的情形;回购价随着回收商成本共担比例的提高而提高,随着其利润分享比例的提高而降低;制造商总能从成本共担-利润共享契约中获益,而当成本共担比例适中、利润共享比例较大时,回收商才愿意接受该契约,此时,成本共担-利润共享契约生效且能够协调闭环供应链.     

专利保护下闭环供应链碳减排及协调决策

考虑政府征收碳税及再制造专利保护,建立原制造商和第三方再制造商不同决策情形的博弈模型,探讨碳税、碳减排对制造/再制造决策的影响.研究结果表明:碳税使原制造商收益受损,当再制造产品接受度大于再制造碳排放比率时,碳税使再制造商利润增加;碳减排使新产品产量增加,原制造商利润增加;碳减排使再制造专利许可费提高,不利于废旧产品回收,再制造商利润不一定增加;集中决策下废旧产品的回收率和供应链总利润均高于分散决策,当满足碳税促进再制造的条件时,集中决策具有更好的环境绩效;针对分散决策的效率损失,原制造商收取适当专利许可费,再制造商分担部分减排成本,能够实现闭环供应链的协调.最后,运用数值仿真验证以上结论,并进一步分析碳税和碳排放比率对减排率的影响.     

基于博弈论的再制造逆向物流定价决策

针对再制造逆向物流定价决策问题,探讨在垄断回收模式和竞争回收模式下,受多因素(行业竞争、规模经济、政府补贴、废旧品再制造等)影响的由两个制造商和两个回收商组成的逆向物流系统;建立基于Stackelberg博弈的再制造逆向物流定价决策模型;求解关于决策变量和目标函数的子博弈精炼Nash均衡解,并进行模型参数约束分析、影响因素灵敏度分析、两种回收模式的比较分析以及数值分析.研究结果表明,竞争回收模式比垄断回收模式对各方参与者更为有利,提高废旧品的回收率、再制造率以及政府补贴有利于逆向物流系统的发展.     

逆向物流多产品两阶段再生产网络鲁棒优化

考虑不同周期内逆向物流回收数量的不确定性和再生产设备的生产能力约束,将逆向物流回收数量、再生产成本和市场需求作为不确定参数,以成本最小为目标,建立了包含生产成本、设备运作成本、库存成本在内的多周期多产品两阶段逆向物流网络鲁棒优化模型。通过算例验证了模型的有效性。     

基于EPR制度的企业再制造决策

考虑生产者延伸责任制度在我国再制造产业的实施,构建由一位制造商与一位再制造商组成的闭环供应链动态博弈模型,以成员企业的回收努力水平、废旧产品购买量、产品产量等为决策要素,分别探讨无政府参与的自由回收、基于回收率奖惩的政府规制以及政府规制下的基金调控3种模式下制造商与再制造商的最优决策,分析政府规制与基金调控对企业决策和环境绩效的影响.研究表明:制造商的回收策略与废旧产品的转移价格密切相关;基于回收率奖惩的政府规制对回收再制造活动具有积极的推进作用;再制造基金调控在一定程度上能够激励再制造商提高生产能力,有利于专业分工局面的形成,但不适于在再制造产业成熟阶段实施.研究结论对生产者延伸责任制度下企业再制造策略选择、政府环境规制设计具有一定的参考价值.     

基于回收产品质量水平的闭环供应链渠道选择模型

基于回收努力和回收产品质量水平的考虑,应用Stackelberg博弈模型理论,构建分别由制造商回收、零售 商回收和第三方回收的3种再制造闭环供应链决策模型,考察不同渠道下参与主体最优决策差异和基于回收产品 质量水平的回收渠道选择问题.结果表明,第三方回收为下策均衡,制造商回收或零售商回收取决 于产品再制造成本的节约水平,制造商需衡量其再制造成本,从制造商回收和零售商回收中选择最优的回收渠道.     

基于微分博弈的供应链合作减排和政府补贴策略

低碳背景下,将产品的减排量作为状态变量,借助微分博弈研究由供应商和制造商组成的两级供应 链长期动态合作减排和政府补贴策略问题.分别构建集中式和无成本分担的分散式微分博弈模型,并通过引入成本分担契约实现供应链系统利润的Pareto改善,得出并比较了3种决策情形下供应商和制造商各自相应的最优反馈均衡策略,以及产品减排量随时间变化的最优轨迹;然后,讨论政府补贴行为与企业选择合作减排行为之间的互动博弈,发现政府减排补贴的引入改变了3种决策情形下供应链成员的最优减排努力水平和利润的大小;最后,通过算例对相关参数进行灵敏度分析,验证了结论的有效性,为供应链上下游企业长期开展合作减排以及政府制定补贴政策提供了科学依据.     

不确定条件下配送回收中心选址配送问题研究

针对制造商、零售商、一个废弃处理中心和多个配送回收中心构成的闭环供应链,解决模糊随机环境下的配送回收中心选址配送问题。引用模糊随机理论处理产品回收率和可再利用率随机变量,以成本最低和碳排放最小为双重目标,以设施能力,设施间流量以及设施数量为约束,建立多目标闭环供应链配送回收中心选址配送模型。改进了全局-局部-邻域粒子群算法,设计了基于优先级的全局-局部-邻域粒子群算法方案,并用案例验证了模型及算法的有效性和先进性。     

基于第三方回收再制造逆向物流网络设计

针对再制造逆向物流网络设计问题, 在考虑产品回收量和消费市场需求量不确定的条件下, 以第三方物流企业收益最大化和制造商收益最大化为目标建立了基于第三方回收多周期再制造逆向物流网络模型. 利用该模型可以确定每个周期制造商购买第三方物流企业产品的最优价格, 可以确定网络中回收中心和检测/拆卸中心的开设数量以及各设施间的物流量分配. 将不确定参数用三角模糊数表示, 借助模糊机会约束规划方法将该模型转化为确定性等价模型. 利用算例验证了模型的有效性, 并用目标规划法分析了两个目标之间的关系.     

零售电商和回收政策对闭环供应链的影响研究

构建第三方回收下的双渠道闭环供应链模型,考虑了三种不同的决策情形来探讨零售电商参与和处理基金政策对供应链中决策、利润、需求和消费者剩余的影响。结果表明：零售电商参与使得传统零售商的产品价格和利润水平降低,制造商可以通过调整对零售电商的批发价格来提高其利润;第三方回收商的回收决策和最优利润不受到零售电商参与的影响,处理基金政策可以有效地提高产品回收数量,但也会使得正向供应链中企业的定价提高;零售电商会蚕食制造商原有的市场份额,但产品总需求量不发生变化。当进一步考虑处理基金政策时,市场总需求量出现下降的趋势;此外,零售电商参与和处理基金政策都会造成供应链中消费者总剩余的减少。     

A linear model for compound multicommodity network flow problems

This work proposes a network flow linear program model to solve the problem of minimizing costs of production and distribution of compound multicommodities. In our proposed model, coupling constraints are considered in order to treat the existing proportionality among several flows of different commodities that are necessary to mixture for composing new commodities. The coupling constraint matrix for this type of problem is very large in general. Our formulation reduces the number of proportionality constraints enabling the use of a solution technique based on a specialization of the primal-dual simplex algorithm applied in two distinct phases. As initial solution it is used a basis built through the heuristic method that allocates flows in low cost lanes. To perform the change of basis operation, the working matrix is stored as a product form of the inverse to keep constant its dimension and to preserve sparsity. Experimental results containing around 200,000 constraints and 75,000 arcs applicable to the distribution of multicommodities of a petrochemical industry were accomplished with success. The results obtained show computer efficiency of the developed algorithm and the applicability of the formulated model.     

随机需求和奖惩机制下的闭环供应链决策模型

研究新产品和再制造产品需求均为不确定下的闭环供应链系统。通过比较两种产品的消费者WTP(willing to pay)差异性,构建三种政府奖惩机制条件下的闭环供应链模型。深入分析不同制造商主导的博弈模型及其数值实验。结果表明:无论是基于回收率还是回收量的政府奖惩机制,第三方回收模式下回收率最高,制造商利润最高,制造商回收模式下零售商利润最高;消费者对再制造产品WTP差异增加时,制造商利润、零售商利润及渠道总利润先减少后增加;政府奖惩机制变化时,第三方回收模式的回收率随政府奖惩的增加而增幅最大。     

Economic optimization using model predictive control with a terminal cost

In the standard model predictive control implementation, first a steady-state optimization yields the equilibrium point with minimal economic cost. Then, the deviation from the computed best steady state is chosen as the stage cost for the dynamic regulation problem. The computed best equilibrium point may not be the global minimum of the economic cost, and hence, choosing the economic cost as the stage cost for the dynamic regulation problem, rather than the deviation from the best steady state, offers potential for improving the economic performance of the system. It has been previously shown that the existing framework for MPC stability analysis, which addresses to the standard class of problems with a regulation objective, does not extend to economic MPC. Previous work on economic MPC developed new tools for stability analysis and identified sufficient conditions for asymptotic stability. These tools were developed for the terminal constraint MPC formulation, in which the system is stabilized by forcing the state to the best equilibrium point at the end of the horizon. In this work, we relax this constraint by imposing a region constraint on the terminal state instead of a point constraint, and adding a penalty on the terminal state to the regulator cost. We extend the stability analysis tools, developed for terminal constraint economic MPC, to the proposed formulation and establish that strict dissipativity is sufficient for guaranteeing asymptotic stability of the closed-loop system. We also show that the average closed-loop performance outperforms the best steady-state performance. For implementing the proposed formulation, a rigorous analysis for computing the appropriate terminal penalty and the terminal region is presented. A further extension, in which the terminal constraint is completely removed by modifying the regulator cost function, is also presented along with its stability analysis. Finally, an illustrative example is presented to demonstrate the differences between the terminal constraint and the proposed terminal penalty formulation.     

Optimal production decision for a risk‐averse manufacturer faced with random yield and stochastic demand

Consider a risk‐averse manufacturer who produces a single product with a random yield to satisfy uncertain market demand. The manufacturer maximizes its expected profit subject to a chance constraint that requires the probability of the total profit below a target be less than a predetermined level. We show that due to the profit target constraint in the presence of random yield and stochastic demand, the manufacturer can neither produce too much nor too little irrespective of the predetermined probability level, depending solely on the profit target level. Further, the special case of uniform yield and uniform demand is examined and we obtain the manufacturer's optimal production quantity. In addition, two special cases of random yield rate and deterministic demand or deterministic yield rate and stochastic demand are considered. The opposite impacts of random yield and stochastic demand are revealed: the random yield induces a minimum production quantity that may cause the manufacturer to increase its production quantity, while the stochastic demand induces a maximum production quantity that may cause the manufacturer to decrease its production quantity. By comparing the solutions of the above‐mentioned special cases with the case of both random yield and stochastic demand, it is demonstrated that the existence of both random yield and stochastic demand results in a more constrained production requirement for the manufacturer (a larger minimum production quantity and a smaller maximum production quantity). That is, the opposite impacts of random yield and stochastic demand will not offset, but enhance each other.     

Two-echelon fuzzy stochastic supply chain for the manufacturer–buyer integrated production–inventory system

This paper deals with two-echelon integrated procurement production model for the manufacturer and the buyer integrated inventory system. The manufacturer procures raw material from outside suppliers (not a part of supply chain) then proceed to convert it as finished product, and finally delivers to the buyer, who faces imprecise and uncertain, called fuzzy random demand of customers. The manufacturer and the buyer work under joint channel, in which a centralized decision maker makes all decisions to optimize the joint total relevant cost (JTRC) of entire supply chain. In this account, in one production cycle of the manufacturer we determine an optimal multi-ordering policy for the buyer. To be part of this, we first derive the JTRC in stochastic framework, and then extend it in fuzzy stochastic environment. In order to scalarize the fuzzy stochastic JTRC, we use an evaluation method wherein randomness is estimated by probabilistic expectation and fuzziness is estimated by possibilistic mean based on possibility evaluation measure. To derive the optimal policies for both parties, an algorithm is proposed. A numerical illustration addresses the situations of paddy procurement, conversion to rice and fulfillment of uncertain demand of rice. Furthermore, sensitivity of parameters is examined to illustrate the model and algorithm.     

绿色供应链的投贷联动融资决策均衡

以一个零售商和一个资金约束的制造商组成的绿色供应链为研究对象,构建了制造商资金约束情况下银行借贷融资、股权融资和组合融资时的融资模型,探讨制造商的资金水平和消费者的绿色偏好对定价、绿色投入水平、产品的市场需求和融资方式选择策略的影响。最后,通过数值分析进行验证。研究发现：消费者绿色偏好与零售价格、批发价格和绿色投入努力水平、产品的市场需求和股权融资时双方可接受的股权转让比例正相关;在制造商资金约束而不融资时,制造商初始资金水平与制造商的批发价格、零售商的零售价格负相关,而与绿色投入努力水平正相关;银行借贷利率越大,制造商的可接受的股权转让比例增大。当制造商进行融资时, 若初始资金水平极低, 选择股权融资的方式进行融资, 随着初始资金水平的上升, 零售商应该选择银行贷款的方式进行融资;在股权融资比例达到一定值时,组合融资比银行借贷更加有利于制造商;而单纯股权融资比组合融资更有利。     

考虑客户聚类与产品回收的两级闭环物流网络选址-路径优化

针对目前不合理的废旧产品回收以及物流活动产生的碳排放污染，提出了一种考虑客户聚类与产品回收的两级闭环物流网络选址-路径优化模型。首先，结合实际物流网络的动态性假设客户需求量和回收率的不确定性特征，以最小运营成本和最小环境影响为目标建立选址-路径优化模型；其次，对多目标进化算法进行改进，提出了考虑客户聚类结果的两级物流设施选址-路径问题求解算法；最后，对该优化算法进行算法性能分析，并以重庆市某企业为例进行了模型和算法验证。结果表明，所建立的模型和算法能有效降低决策难度并提高物流系统的运作效率，所求出的优化方案能减少物流运作成本和降低物流运输过程对环境的影响。     

Deterministic inventory lot-size models with shortages for fluctuating demand and unit purchase cost

The classical economic order quantity (EOQ) model assumes not only a constant demand rate but also a fixed unit purchasing cost. In today's time‐based competition, the unit cost of a high‐tech product declines significantly over its short product life cycle while its demand increases. Therefore, using the classical EOQ formulation for a high‐tech product will cause varying magnitudes of error. In addition, the cost of purchases as a percentage of sales is often substantial. Consequently, adding the purchasing strategy into the EOQ model is vital. In this paper, we assume that not only the demand function but also the unit purchase cost is fluctuating with time. We then provide an easy‐to‐use algorithm to find the optimal replenishment number and schedule. In a numerical example, we show that the total cost obtained by our proposed model is 32.4% less expensive than that obtained by the classical EOQ model.     

Optimal manufacturer's pricing and lot-sizing policies under trade credit financing

In this paper, we extend Goyal's economic order quantity (EOQ) model to allow for the following four important facts: (1) the manufacturer's selling price per unit is necessarily higher than its unit cost, (2) the interest rate charged by a bank is not necessarily higher than the manufacturer's investment return rate, (3) the demand rate is a downward‐sloping function of the price, and (4) an economic production quantity (EPQ) model is a generalized EOQ model. We then establish an appropriate EPQ model accordingly, in which the manufacturer receives the supplier trade credit and provides the customer trade credit simultaneously. As a result, the proposed model is in a general framework that includes numerous previous models as special cases. Furthermore, we provide an easy‐to‐use closed‐form optimal solution to the problem for any given price. Finally, we develop an algorithm for the manufacturer to determine its optimal price and lot size simultaneously.     

An analysis of consumer training for feature rich products

Many products now are loaded with an enormous number of features. It creates a great challenge for consumers to fully explore functionalities of those products. A recent trend is that manufacturers that market feature rich products start to provide consumer training programs. In this paper, we study the motivation of a manufacturer to offer training to consumers and how the training related costs affect his profits. We use a two dimensional consumer heterogeneity model to capture the consumer's learning cost and valuation of features. We show how training shifts consumer's purchasing decisions and the conditions under which the manufacturer is motivated to offer training. Two specific situations are investigated: when training is required and when training is optional. We show that if the manufacturer can effectively and cost efficiently deliver the training program, then optional training can make the product more attractive and improve the manufacturer's net gains the most. Our results also indicate that the availability of online educational tools is one of the reasons for recent trend in consumer training.