具有风险规避型零售商的闭环供应链网络均衡分析

在随机需求条件下研究了由多个相互竞争的供应商、制造商、零售商和消费市场组成,且零售商具有风险规避特性的再制造闭环供应链网络均衡问题.通过对不同决策层级最优化行为的分析,分别得到各层级和整个供应链网络实现均衡的条件,并建立相关的变分不等式模型.运用拟牛顿算法对变分不等式进行求解,通过仿真分析了随机再制造率和零售商的风险规避程度对网络成员最优行为和闭环供应链网络均衡的影响.     

供应链网络双渠道均衡

研究了制造商通过分销商实体链和电子商务直销渠道,将其产品经由零售商销售给具有随机需求的消费市场的供应链网络双渠道均衡问题.利用有限维变分不等式理论,分别刻画了存在生产能力限制的供应市场、分销市场、零售市场以及存在限定性价格上限的消费市场的均衡,建立了整个供应链网络双渠道均衡模型,并且设计了供应链网络双渠道均衡的投影收缩算法.数值算例结果表明:当政府对竞争市场实行限制性价格上限时,将造成消费市场中的商品短缺,并导致制造商、分销商以及零售商的总利润减少,当存在产能约束时情况更为严重.     

具有损失规避零售商的模糊供应链网络均衡

针对模糊市场需求情形,研究具有损失规避行为零售商的无缺货成本的供应链网络均衡问题。利用模糊事件的可信性测度理论,推导具有分段线性效用函数损失规避零售商的模糊期望效用模型,揭示其凹性性质。利用变分不等式理论,描述制造商、零售商和消费者的最优行为,进而构建网络均衡模型。为了简化网络均衡条件,揭示了制造商与零售商内生交易定价机制的等价关系。最后,利用数值分析表明了市场需求的模糊性和损失规避系数对网络均衡的影响。     

损失概率厌恶和损失厌恶行为零售商的供应链网络均衡

研究零售商的损失概率厌恶和损失厌恶有限理性行为对供应链网络均衡的影响. 利用变分不等式和互补理论刻画制造商的最优行为和需求市场的供需均衡; 基于累积前景理论建立零售商的凹前景值函数, 并利用变分不等式刻画零售市场均衡. 零售商有限理性行为对其均衡行为的比较静态分析结果表明: 零售商的最大损失重视程度越大, 其均衡订购量越小; 零售商的最大获利重视程度越大, 其均衡订购量越大; 零售商的损失概率敏感度越大, 其均衡订购量越小; 零售商的损失厌恶程度越大, 其均衡订购量越小.

     

电子商务下全球闭环供应链超网络模型

建立了一个由制造商、零售商、消费者与回收商构成的全球闭环供应链超网络均衡模型.回收商回收、处置废弃产品、并将生产出的新产品销售给零售商与消费者.模型中的交易方式包括传统交易与网上交易.考虑有多种交易货币,模型设定了不同货币对基础货币的增值率.首先对各层决策者的行为进行了研究,探计了它们之间的相互作用,又运用变分不等式的...     

随机需求下闭环供应链网络设施竞争选址模型研究

利用均衡理论和变分不等式研究工具,建立了随机需求情形下多层竞争型闭环供应链网络均衡模型,并在此基础上,构建了均衡约束数学规划模型,即设施竞争选址模型.利用均衡模型来捕捉由新进设施的进入所引起的网络均衡状态的变化,并将其引入位置决策过程.根据模型特点,提出了遗传算法与修正投影算法相结合的求解策略.最后利用提出的模型和求解算法对算例进行计算与分析,得到了网络竞争趋势变化情况、新设施的位置策略及其生产运营决策.     

基于随机需求的区域血液供应系统优化

从供应链一体化的角度对区域血液供应网络建模。采用多目标规划的方法,将血液采集风险成本、系统运作成本、供给过多与过少的惩罚成本最小作为目标,考虑血液报废量与时间成正比的特性,将过期报废血液处理费用考虑在内,建立了随机需求的四种血型的区域供需网络均衡模型。通过证明所建模型是凸的,进一步导出了血液供需网络平衡的变分不等式。运用修改的拟牛顿法,求得了随机需求下血液供应链供需平衡的解。最后,通过成都某区供血系统进一步验证了模型的适用性。     

随机需求下多风险偏好零售商的供应链库存决策和协调

考虑由单个风险中性供应商和?? 个风险偏好零售商组成的供应链系统. 假设市场需求是随机的, 且每个零售商面临的需求与其订货量成正比, 采用平均CVaR 准则刻画零售商的风险偏好. 当零售商对称时, 得到系统总的均衡订货量关于零售商数量和风险偏好系数的单调性; 证明当风险偏好系数满足一定条件时, 批发价契约可以使供应链协调; 随机大需求导致系统较高的均衡订货量. 最后通过数值例子表明了需求可变性对系统总的均衡订货量的影响.

     

社区便利O2O的供应链超网络均衡模型研究

针对社区便利O2O自身的特征,构建了由供货商、各合作门店以及小区市场组成的三层供应链超网络模型。分析模型中各决策者的行为以及优化条件,利用变分不等式理论求解整个网络达到均衡状态的条件。设计算例并进行数值仿真,探讨了关系价值重视度以及网络渠道的接受程度对整个供应链均衡决策的影响,验证了模型的有效性,为社区便利O2O供应链的稳定发展提供科学的分析依据。     

考虑交通拥堵成本的零售商供货量决策模型

引入交通拥堵成本因子,考虑从零售商配送中心到市场间的路段存在交通拥堵情况下,分别建立了供应链系统中供应商定价模型和零售商供货量模型;运用动态博弈分析方法,得出了零售商和供应商满足利润最大化条件下解的均衡方程;最后,研究了一个简化的供应链网络,对上述模型进行了验证与分析。结果表明,随着交通拥堵成本因子的不断增大,零售商会逐渐减少对市场的商品供货量,通过提高市场价格和减少运输费用来弥补拥堵成本的增加。     

Service cooperation and marketing strategies of infomediary and online retailer with eWOM effect

In contemporary electronic commerce, an infomediary displays electronic word-of-mouth (eWOM) information of customers and links shoppers to retail websites, thus acting as an intermediary between buyers and sellers. This paper studies an online supply chain system in which the infomediary presents demand-referral services to online retailers based on eWOM of customer information. It is assumed that online demand is affected by retailer price, referral service effort, and eWOM. The demand function is extended and developed based on Bass’s model. A Stackelberg game model of service cooperation is presented, and then the optimal decisions on retailers’ prices and infomediary service efforts in the decentralized supply chain are analyzed. Moreover, the profits and cumulative sales in supply chain equilibrium are analyzed under several parameters. A computational experiment is implemented to verify the validity and effectiveness of the model. The results show that price sensitivity has a significant negative effect on cumulative retailer sales and the profits of retailers and infomediary, but the effect of service sensitivity and sales periods on profits is absolutely positive. Specifically, eWOM has two different impacts on the profit of the retailer and infomediary respectively. Finally, conclusions and management implications for supply chain parties are presented, along with some possible directions for further research.     

Pricing,manufacturing and inventory policies for raw material in a three-level supply chain

We studied a decentralised three-layer supply chain including a supplier, a producer and some retailers. All the retailers order their demands to the producer and the producer order his demands to the supplier. We assumed that the demand is price sensitive and shortage is not permitted. The goal of the paper is to optimise the total cost of the supply chain network by coordinating decision-making policy using Stackelberg–Nash equilibrium. The decision variables of our model are the supplier's price, the producer's price and the number of shipments received by the supplier and producer, respectively. To illustrate the applicability of the proposed model numerical examples are presented.     

考虑产品替代的低碳供应链定价和政府财税

基于低碳经济背景,考虑由政府、制造商和零售商三方博弈构成的供应链,使用Stackelberg博弈和纳什均衡的分析方法求出模型的均衡解,并对比了零售商是否联合两种模式下的社会福利、制造商和零售商利润。结果表明：零售商联合情况下的零售商和制造商利润大于零售商非联合情形,同时产品需求量和社会福利与零售商非联合情形相同。高碳产品市场规模越大,社会福利、零售商和制造商利润会先下降后上升,低碳产品的生产成本增加,社会福利、制造商利润会下降,若零售商不联合,销售高碳产品零售商利润上升,销售低碳产品零售商利润下降,若零售商联合则零售商利润下降。     

模糊环境下考虑零售商风险偏好的绿色供应链博弈模型

在模糊需求环境下绿色供应链运作系统中,研究由单一制造商和单一零售商组成的两级绿色供应链.首先,引入创新成本,分别建立风险中性制造商为主导者,具有中性、悲观和乐观等风险偏好的零售商为跟随者的两级绿色供应链Stackelberg博弈模型;然后,推导出最优决策的期望值和机会约束规划模型,并进行算例分析,比较产品绿色度、批发价格及零售价格与不同置信水平之间的相互影响,探讨具有不同风险偏好的零售商对模糊绿色供应链中制造商、零售商及供应链整体运作绩效的影响.研究结果表明:悲观决策模型中,伴随置信水平的增加,产品的绿色度水平、批发价格及创新成本逐步下降,零售价格、制造商、零售商及绿色供应链整体利润逐步上升;在乐观决策模型中,结论相反.     

An integration methodology based on fuzzy inference systems and neural approaches for multi-stage supply-chains

This paper proposes a methodology for supply chain (SC) integration from customers to suppliers through warehouses, retailers, and plants via both adaptive network based fuzzy inference system and artificial neural networks approaches. The methodology presented provides this integration by finding the requested supplier capacities using the demand and order lead time information across the whole SC in an uncertain environment. The SC structure is investigated stage by stage. The sensitivity analysis is made by comparing the obtained results with the traditional statistical techniques. A company serving in durable consumer goods industry that produces consumer electronics in Istanbul, Turkey was examined to demonstrate the applicability of the proposed methodology.     

Two parameter tuned multi-objective evolutionary algorithms for a bi-objective vendor managed inventory model with trapezoidal fuzzy demand

This paper presents a bi-objective vendor managed inventory (BOVMI) model for a supply chain problem with a single vendor and multiple retailers, in which the demand is fuzzy and the vendor manages the retailers’ inventory in a central warehouse. The vendor confronts two constraints: number of orders and available budget. In this model, the fuzzy demand is formulated using trapezoidal fuzzy number (TrFN) where the centroid defuzzification method is employed to defuzzify fuzzy output functions. Minimizing both the total inventory cost and the warehouse space are the two objectives of the model. Since the proposed model is formulated into a bi-objective integer nonlinear programming (INLP) problem, the multi-objective evolutionary algorithm (MOEA) of non-dominated sorting genetic algorithm-II (NSGA-II) is developed to find Pareto front solutions. Besides, since there is no benchmark available in the literature to validate the solutions obtained, another MOEA, namely the non-dominated ranking genetic algorithms (NRGA), is developed to solve the problem as well. To improve the performances of both algorithms, their parameters are calibrated using the Taguchi method. Finally, conclusions are made and future research works are recommended.     

A Closed-Loop Supply Chain Equilibrium Model with Random and Price-Sensitive Demand and Return

This paper proposes a decentralized closed-loop supply chain network model consisting of raw material suppliers, manufacturers, retailers, and recovery centers. We assume that the demands for the product and the corresponding returns are random and price-sensitive. Retailers and recovery centers face penalties associated with shortage demand and supply, respectively. We derive the optimality conditions of the various decision-makers, and establish that the governing equilibrium conditions can be formulated as a finite-dimensional variational inequality problem. The qualitative properties of the solution to the variational inequality are discussed. Numerical examples are provided to illustrate the effects of demand and return uncertainties on quantity shipments and prices.