具有高投标成本的多属性逆向拍卖博弈模型

越来越多像GE这样的大型企业在利用多属性逆向拍卖选择新的供应商采购产品时,通常会设定较高的固定投标成本。针对此情况,建立了三阶段的非合作博弈模型,并利用求解子博弈纳什均衡策略的方法,推导出了供应商的最优投标价格。并得到以下两个主要结论:一是供应商的最优投标策略是按照生产产品真实的质量和交货期进行投标,且投标价格为最优投标价格;二是采购商的最优策略是选择投标价格最高的供应商作为拍卖获胜者,这一违反直觉的结论。这是合理的,因为投标价格最高的供应商也是类型最优的供应商,也即投标质量和投标交货期组合最优的供应商。最后,利用数值实验验证了模型的有效性,并显示出设定相对较高的固定投标成本对采购商来说是有利的。     

多主体参与下企业技术创新模式动态选择研究

多主体参与已经成为现代经济环境下企业创新活动的基本特征。为了明确各创新主体参对企业创新模式选择的影响。本文构建了一个包括供应商和顾客参与的创新模式选择博弈模型。对模型分析发现,根据企业选择的创新模式不同,可以形成三种竞争市场,采用演化博弈方法对模型均衡结果求解,得到以下结论:供应商和顾客参与能增加企业选择突破性技术创新模式的比重,减少选择渐进性技术创新比重,且这种影响随着市场中选择突破性技术创新比例增加而增加;当创新产品为价格弹性需求时,顾客参与更能促进突破性技术创新,当创新产品为价格非弹性需求时,供应商参与更能促进突破性技术创新,这与渐进性技术创新的结论截然相反。采用数值算例对结果进行分析,进一步验证了上述结论。本文的研究结论有助于揭示多主体参与对创新模式选择的影响,也对在多主体参与条件下,企业的创新资源配置这一创新的核心问题做出了一定的解释。     

考虑不同碳排放处理模式的动态供应商选择及采购批量问题研究

不同的碳排放处理模式及不确定的市场需求等因素影响下,如何选择供应商并确定采购批量直接影响企业的运营和效益。本文在多时间周期、多产品种类、多供应商及随机需求情形下,同时考虑不同碳排放处理模式,分析动态供应商选择及采购批量等最优决策问题,构建混合整数非线性规划模型。通过设计变异算子和扰动因子来改进粒子群算法,力求在短时间内求解大规模决策问题。针对不同规模供应商选择及采购批量决策问题,采用精确方法、近似方法和改进粒子群算法求解。数值实验验证了模型及改进粒子群算法的有效性和可行性,分析了碳税、碳交易价格及碳限额对供应链管理的影响,并给出了供应商选择及碳排放处理的决策参考建议。     

A公司基于TOPSIS法的供应商评价体系研究

作为制造型企业生产链中的关键,供应链管理也显得尤为重要,传统的以价格和质量来评价供应商的方法已不适用当前的市场环境中。所以,结合企业实际提出有效的管理和评价手段就尤为重要。本文利用A显示光源公司的相关指标数据对模型进行分析以及有关供应商接近度的计算结果,区别处于不同级别的供应商分配采购比例并结合企业的管理现状和供应商的产能、公司所在地、战略发展需要等方面的要求,将供应商分类。根据评价结果将A公司的备选供应商按照重要性分为核心供应商、长期供应商、一般供应商和临时供应商。结合评价模型分析为今后A公司供应商的选择提供一定的参考意见。     

软计算方法在供应商选择多回合博弈过程中的应用

供应商的选择是一个协作双方联盟博弈的过程。在这一过程中,供应商的主观博弈策略和客观因素的变动都有可能导致博弈过程动态性的产生。通过将博弈过程合理分段,并采用软计算方法中的模糊隶属函数分别描述博弈子过程特征和供应商指标变动特征,提出了以多回合博弈过程为变量的综合评价函数选择方法。最后,通过实例分析,得到了满意的结果。     

多属性采购拍卖的价值函数与打分规则

在多属性采购中,采购方不仅关心交易价格,更加关注供应商的交货时间和提供的装备质量对其价值的影响。为综合评价供应商的投标,采购方在采购拍卖开始时宣布一个打分规则。本文根据装备采购实践建立多属性采购拍卖的价值函数,以此为基础构建集成了质量属性、提前期属性和价格的三元打分规则。     

基于消费者效用的生鲜农产品供应链生鲜度激励机制研究

生鲜供应链整体生鲜度的提升对减少浪费、提高供应链整体盈利水平及社会福利有重要意义。本文基于消费者效用理论研究了两供应商和单一零售商组成的供应链系统，构建了单周期下生鲜农产品生鲜度激励模型，模型以供应商为领导者，采用Stackelberg博弈方法求解得到了均衡状态下供应商、零售商的最优定价策略及供应商新鲜度努力选择。研究结果表明，供应商和零售商利润与消费者价格敏感系数呈反向变化，与新鲜度敏感系数呈同向变化。在价格竞争市场，供应商保鲜努力程度和利润与价格替代率呈反向变化；在生鲜度竞争市场，供应商保鲜努力程度和利润与新鲜度替代率呈同向变化。基于研究结论，厂商及政府应当联手引导消费者的消费观念，尽可能减少由于信息不对称引致的道德风险，在市场价格替代率不变甚至降低的情形下，提高生鲜度替代率，使得消费者的意愿支付价格上升，提高自身讨价还价能力，获取更多利润。     

具有激励特征的供应商动态评价方法

在建立供应链合作关系之前,对供应商的评价、选择是企业的重要决策问题之一.本文首先提出了一套评价供应商的指标体系,并在应用一种无需一致性检验的方法G1法的基础上,提出具有激励特征的供应商动态评价方法,体现对不同时期供应商业绩改善的激励,以促进供应商不断提高业绩,更好地加强制造商与供应商的合作关系.     

供应商优选的多目标混合整数规划模型

供应商评价和选择是全球制造和全球竞争的需要.在运营管理文献中,供应商优选和评价已经成为主要话题之一.建立了多目标整数规划模型,试图实现在满足多约束条件下,供应商选择的多目标权衡优选问题,并对一些大型重要企业进行了调研,对此模型进行实证检验.     

基于多属性逆向拍卖的博弈分析

对只有一个采购商和多个供应商之间进行的单轮多属性逆向拍卖建立了非合作博弈模型,分析得出投标具有最高质量和最短交货期属性的供应商能够获得最大利润,同时能够给采购商带来最大剩余.因此采购商并不会根据最低投标价格,而是根据投标质量和交货期的最优组合来选择新的供应商.然后,把投标价格看作投标质量和交货期的函数,推导出了供应商的最优投标价格策略,并进一步推出纯子博弈纳什均衡策略.最后,通过算例验证了模型的有效性,并指出采购商在利用多属性逆向拍卖进行采购之前,应该对供应商资格进行审核来决定最后能够参与到拍卖中的供应商数目.     

An analysis of the supplier selection process

Customers select suppliers based on the relative importance of different attributes such as quality, price, flexibility, and delivery performance. This study examines the difference between managers' rating of the perceived importance of different supplier attributes and their actual choice of suppliers in an experimental setting. We use two methods: a Likert scale set of questions, to determine the importance of supplier attributes; and a discrete choice analysis (DCA) experiment, to examine the choice of suppliers. The results indicate that although managers say that quality is the most important attribute for a supplier, they actually choose suppliers based largely on cost and delivery performance.     

考虑供应商产品交付水平的供应链融资策略研究

供应商产品的交付水平直接影响下游制造商的生产，但是这种现象没有得到供应链金融研究的重视。为此，本文将供应商交付水平和供应链的运营融资问题结合起来研究。在考虑供应商产品交付水平的情况下，通过研究资金不足的供应商分别利用制造商预付款融资和风险投资方股权融资时，供应商的最优运营决策和融资策略，最后考虑了供应商对两种融资方式的选择。研究结果表明，供应商的自有资金水平对供应链均衡决策及其收益影响很大，有限的自有资金严重制约了供应商产品的交付水平，降低了供应链的运作效率；不管是资金充足，还是选择融资，供应商的利润不仅与自身的运营效率有关系，而且与替代供应商产品的批发价格有很大关系，当供应商的运营效率较低时，供应商的利润随着替代供应商产品的批发价格先增大后减小，当供应商运营效率较高时，供应商的利润随着替代供应商产品的批发价格逐渐增大。当供应商进行融资时，若自有资金水平较低，应通过股权融资的方式进行融资，若自有资金水平较高，供应商应该选择制造商预付款的方式进行融资，若自有资金量超过预付款融资时供应商所需资金的阈值时，供应商选择不融资。     

Single vs. multiple objective supplier selection in a make to order environment

The problem of allocation of orders for custom parts among suppliers in make to order manufacturing is formulated as a single- or multi-objective mixed integer program. Given a set of customer orders for products, the decision maker needs to decide from which supplier to purchase custom parts required for each customer order. The selection of suppliers is based on price and quality of purchased parts and reliability of on time delivery. The risk of defective or unreliable supplies is controlled by the maximum number of delivery patterns (combinations of suppliers delivery dates) for which the average defect rate or late delivery rate can be unacceptable. Furthermore, the quantity or business volume discounts offered by the suppliers are considered. Numerical examples are presented and some computational results are reported.     

A high-quality-supplier selection model for supply chain management and ISO 9001 system

Supplier selection process for supply chain management (SCM) and ISO 9001 quality management system environments is considered. Determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions is usually complex and unstructured. This paper proposes a high-quality-supplier selection (HQSS) model to deal with supplier selection problems in supply chain management. In selecting a supplier, quality management factors are considered first, and then price, delivery, etc. Quality management factors include a quality management audit, product testing, engineering work force, capability index, training time, etc., based on a five-interval scale. Next, the HQSS model determines the final solution by considering factors such as price, production lead-time, and delivery time.     

Improving supplier performance using a comprehensive scheme

Improving and coordinating buyer and supplier efforts to increase productivity and competitive advantage in a supply chain is an important issue. Numerous studies have proposed models, principles and criteria for supplier evaluation and selection. Hence, evaluating and improving supplier performance are important when building long-term supply chain competitiveness. This study presents a novel and comprehensive framework that illustrates the linkages between evaluating supplier performance and planning improvements. The proposed framework comprises four parts: building an evaluation model, evaluating supplier performance based on the buyer perspective, evaluating supplier performance based on the supplier perspective and scheduling improvement tasks. This study applies a hybrid genetic algorithm to help suppliers schedule improvement tasks based on the evaluation findings. Finally, evaluation data of a light-emitting diode (LED) manufacturer in Taiwan is used to interpret the procedure and verify model effectiveness.     

The optimal number of suppliers considering the costs of individual supplier failures

This paper utilizes the decision tree approach to determine the optimal number of suppliers in the presence of supplier failure risks. Previous proposed models have considered only two states of nature: all suppliers fail to deliver and not all suppliers fail to deliver. In practice, however, there is clearly a partial loss associated with the failure of any individual supplier. We present models that allow a more realistic decision-making process by taking into consideration the independent risks of individual supplier failures when the probability of failure for each of the suppliers is equal as well as the case where the probability of failure from each of the suppliers is not equal. We also consider various levels of supplier failure probability and possible procurement or operating cost savings gained from using less reliable suppliers. The results indicate that when suppliers are highly reliable, sole sourcing is the lowest cost approach under all experimental conditions. However, as the suppliers become less reliable, additional suppliers may be required to obtain the lowest cost. Finally, it was shown that only in the extreme conditions of unreliable suppliers, high loss to operational cost per supplier, and low ability to mitigate the failure from a partial set of suppliers, having a large number of suppliers is an effective strategy.     

基于供应商参与新产品开发的供应商选择影响因素分析及实证研究

供应商参与新产品开发(Supplier Involvement in New Product Development,SINPD)已受到越来越多国内外企业的关注,选择合适的供应商参与新产品开发成为企业实施SINPD的关键。以我国制造企业为研究对象,通过对国外相关文献的分析提炼出供应商选择的影响因素,据此设计了问卷量表,利用调研数据进行统计分析验证。研究表明,供应商技术能力、供应商的信誉及企业特征、供应商的合作经历、双方合作兼容性、供应商情景及合作的意愿是我国制造企业选择供应商的关键影响因素。     

Selection of supply portfolio under disruption risks

This paper deals with the optimal selection of supply portfolio in a make-to-order environment in the presence of supply chain disruption risks. Given a set of customer orders for products, the decision maker needs to decide from which supplier to purchase custom parts required for each customer order to minimize total cost and mitigate the impact of disruption risks. The selection of suppliers and allocation of orders is based on price and quality of purchased parts and reliability of delivery. The two types of disruption scenarios are considered: scenarios with independent local disruptions of each supplier and scenarios with local and global disruptions that may result in all suppliers disruption simultaneously. The problem is formulated as a single- or bi-objective mixed integer program and a value-at-risk and conditional value-at-risk approach is applied to control the risk of supply disruptions. The proposed portfolio approach is capable of optimizing the supply portfolio by calculating value-at-risk of cost per part and minimizing expected worst-case cost per part simultaneously. Numerical examples are presented and some computational results are reported.     

Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing

This paper presents a stochastic mixed integer programming approach to integrated supplier selection and customer order scheduling in the presence of supply chain disruption risks, for a single or dual sourcing strategy. The suppliers are assumed to be located in two different geographical regions: in the producer's region (domestic suppliers) and outside the producer's region (foreign suppliers). The supplies are subject to independent random local disruptions that are uniquely associated with a particular supplier and to random semi-global (regional) disruptions that may result in disruption of all suppliers in the same geographical region simultaneously. The domestic suppliers are relatively reliable but more expensive, while the foreign suppliers offer competitive prices, however material flows from these suppliers are more exposed to unexpected disruptions. Given a set of customer orders for products, the decision maker needs to decide which single supplier or which two different suppliers, one from each region, to select for purchasing parts required to complete the customer orders and how to schedule the orders over the planning horizon, to mitigate the impact of disruption risks. The problem objective is either to minimize total cost or to maximize customer service level. The obtained combinatorial stochastic optimization problem will be formulated as a mixed integer program with conditional value-at-risk as a risk measure. The risk-neutral and risk-averse solutions that optimize, respectively average and worst-case performance of a supply chain are compared for a single and dual sourcing strategy and for the two different objective functions. Numerical examples and computational results are presented and some managerial insights on the choice between the two sourcing strategies are reported.     

Selection of resilient supply portfolio under disruption risks

This paper deals with the optimal selection and protection of part suppliers and order quantity allocation in a supply chain with disruption risks. The protection decisions include the selection of suppliers to be protected against disruptions and the allocation of emergency inventory of parts to be pre-positioned at the protected suppliers. The decision maker needs to decide which supplier to select for parts delivery and how to allocate orders quantity among the selected suppliers, and which of the selected suppliers to protect against disruptions and how to allocate emergency inventory among the protected suppliers. The problem objective is to achieve a minimum cost of suppliers protection, emergency inventory pre-positioning, parts ordering, purchasing, transportation and shortage and to mitigate the impact of disruption risks by minimizing the potential worst-case cost. As a result a resilient supply portfolio is identified with protected suppliers capable of supplying parts in the face of disruption events. A mixed integer programming approach is proposed to determine risk-neutral, risk-averse or mean-risk supply portfolios, with conditional value-at-risk applied to control the risk of worst-case cost. Numerical examples are presented and some computational results are reported.