基于信息熵多属性决策的物流供应商选择评价

 生产商选择合适的物流供应商有利于降低营运成本,提高竞争优势.高效的第三方物流活动在增强企业核心竞争力、降低企业成本等方面起着重要作用.针对传统的熵值和熵权计算公式的不足,提出改进的熵权计算公式.同时把专家的主观权重和样本自身产生的熵权相结合,通过一定的方式混合加权作为不确定属性的权重.在此基础上结合多属性决策模型建立多属性决策评价方法.该方法将主、客观分析相结合,具有一定的优势：既减少了决策问题的主观性,又使得整个评价过程能够量化,有效解决了第三方物流供应商选择评价中的不确定多属性决策问题.最后通过实例分析证明该方法的可行性和有效性.     

基于犹豫模糊语言术语的供应商多准则群决策研究

针对全球价值链环境下供应商科学决策问题,提出基于不确定语言术语的多准则群决策模型。首先分别提取专家的偏好信息,将偏好信息转化为犹豫模糊语言术语,引入不确定语言变量进行词计算;其次,运用包络算子融合专家的偏好信息形成犹豫模糊语言术语集,设计集成准则权重的相对贴近度进行产品供应商排序,确定最满意供应商;此外,引入信息熵求解决策过程无先验知识的多准则权重;计算结果表明:3种信息熵参数条件下最满意汽车零部件供应商选择结果完全一致,基于相对贴近度值的供应商优劣排序结果相对于信息熵参数变化不敏感;验证了所提模型可行性、有效性和稳定性,为汽车零部件供应商的实际评价与选择提供有益借鉴。     

关于模糊综合评价方法下的供应链合作伙伴选择

在供应链管理环境下，供应商选择是供应链管理中的一个重要环节，供应商选择的科学与否，直接关系到企业的生存与发展，文章综合层次分析法（AHP）和模糊选择，提出了基于层次分析的供应链合作伙伴的模糊选择方法。这种方法通过AHP方法确定各目标权重，用模糊综合评价方法进行评判，既体现决策者的主观意向，又反映了客观的信息，为确定供应链合作伙伴提供了一种综合评价方法。最后给出了一个数值例子来例证该方法的实际应用。     

基于混合改进TOPSIS的装备供应商选择方法

针对评价值为混合信息、专家权重未知的装备供应商选择问题,提出一种新的供应商选择决策方法。将语义评价信息转化为有犹豫度差异的直觉模糊数,根据专家评价犹豫度和相似度确定专家权重,并利用混合改进TOPSIS方法集结评价值,克服了数据类型的不可公度性,使评价结果更为客观。算例表明该方法具有良好的稳定性和合理性,同时考虑了专家评价差异性和不确定性对排序结果的影响,能够为装备采购决策提供有效参考。     

考虑不完全语义信息的风险型供应商选择方法

考虑供应商选择中决策者的风险态度,提出了一种考虑不完全语义决策信息的风险型供应商选择方法。结合二元语义模型和D数获取并处理决策者给出的不确定性和不完全的供应商评价信息,基于D数信息融合模型获取集结后的群决策信息。基于累积前景理论对候选供应商进行评价,考虑市场竞争获取前景价值函数,基于综合前景值最大化优化模型获得的指标权重对供应商进行排序。最后以挖掘机救援与现场维修服务供应商的评价与选择为例,验证了所提方法的有效性。     

基于BP神经网络和DEA的物流供应商选择

把交叉模型的评价结果设定为样本的期望值,将BP神经网络和交叉评价模型有机结合起来,构建了物流供应商选择模型。以2006年22家上市物流供应商的数据为样本进行了研究。该方法从统计数据出发,避免了主观因素对评价结果的影响,使物流供应商选择结果具有相对客观性。实例表明,该选择模型能够确定出备选物流供应商的评价等级和大小,为物流供应商的选择提供了一种新方法。     

考虑专家风险偏好的物流服务供应商选择研究

提出一种考虑决策专家风险偏好与评价指标关联的方法,用以实现物流外包企业对物流服务供应商的选择。首先,组织各决策专家给出可能风险场景下的评估值以及场景概率,并利用累积前景理论获得反映专家风险偏好的综合前景价值;其次,利用2-可加模糊测度以描述评价指标间的独立、互补、冗余等关联关系,并基于Choquet积分集结各评价指标的综合前景价值;而后,综合考虑专家先验信息与所给评估值信息量以确定专家权重;最后,利用TOPSIS法对候选供应商进行优劣排序。通过某制造企业选择物流服务供应商算例验证了该方法的有效性。     

基于犹豫模糊语言信息的权重信息部分可知TOPSIS方法

基于犹豫模糊集和语言变量,给出犹豫模糊语言变量的定义.采用犹豫模糊语言变量建模决策过程中的不确定信息,在考虑属性权重信息部分可知的情况下,提出了一个新的多属性决策方法.首先,利用犹豫模糊语言变量给出方案的评价值.然后,采用极大偏差法建立线性规划模型确定属性权重向量.最后,采用TOPSIS方法对方案进行排序,并且给出了具体的方案排序方法.为了说明新方法的可行性和有效性,我们将其应用到地铁壁画的评价上.实例表明新方法确实是一个简单有效的方法.     

基于贝叶斯方法的包装企业供应商评价与选择模型

目的建立基于贝叶斯方法的供应商选择模型。方法建立一个供应商选择动态过程,将供应商的历史信息与供应商提供的自身信息联系起来;利用贝叶斯方法对供应商达成采购企业目标的能力进行评判和修订,并进一步评估供应商风险。结果贝叶斯方法为包装企业评价和选择供应商提供了规避风险的有效手段,可以提高包装企业的竞争力。结论基于风险视角下的供应商选择与评价模型,是保证包装企业在控制供应商风险的前提下对供应商进行选择评价的重要工具。     

基于最大熵的两级逼近理想点的配送路线选择

供应链配送路线选择是多个节点企业共同决策的结果,对于供应链成员共同决策的评价指标,用最大熵的技术来确定初步的权重.但供应商和零售商对配送路线有不同的偏好与权重.用隶属度的方法来度量供应商对各指标确定的权重,并采用逼近理想点法对供应商的方案进行评判,形成接近度矩阵;在此基础之上,利用隶属度法来度量零售商对各配送路线确定的权重,并采用逼近理想点法对配送路线进行综合评判与选优.以某汽车制造业的供应链配送路线选择决策作为案例,进行了说明与分析.     

A novel multiple attribute material selection approach with uncertain membership linguistic information

In engineering design, the decision to select an optimal material has become a challenging task for the designers, and the evaluation of alternative materials may be based on some multiple attribute decision making (MADM) methods. However, the current methods for material selection may induce the information losing and cannot represent the real preference of decision maker precisely. Therefore, in this paper, inspired by the idea of the intuitionistic linguistic variables, we define a new fuzzy variable called uncertain membership linguistic variable (UMLV) which composes two linguistic variables and membership degrees of elements to the linguistic variables. Meanwhile, the operational laws, score function, accuracy function and comparison rules of the UMLV are defined. Then, some aggregation operators are developed for aggregating the uncertain membership linguistic information such as the uncertain membership linguistic weighted average (UMLWA) operator, the uncertain membership linguistic weighted geometric (UMLWG) operator, the uncertain membership linguistic ordered weighted average (UMLOWA) operator and the uncertain membership linguistic ordered weighted geometric (UMLOWG) operator, and some desirable properties of these operators are discussed. Based on the proposed operators, an approach is proposed for material selection problems under uncertain membership linguistic environment. Finally, two numerical examples for material selection are given to illustrate the application of the proposed approach.     

An interval 2-tuple linguistic MCDM method for robot evaluation and selection

Nowadays selection of an optimal robot has become a challenging task for manufacturers with the increment of production demands and availability of more different robot models. Robot selection for a particular industrial application can be viewed as a complicated multi-criteria decision-making problem which requires consideration of a number of alternative robots and conflicting subjective and objective criteria. Furthermore, decision-makers tend to use multigranularity linguistic term sets to express their assessments on the subjective criteria, and there usually exists uncertain and incomplete assessment information. In this paper, an interval 2-tuple linguistic TOPSIS (ITL-TOPSIS) method is proposed to handle the robot selection problem under uncertain and incomplete information environment. This method considers both subjective judgements and objective information in real-life applications, and models the uncertainty and diversity of decision-makers’ assessments using interval 2-tuple linguistic variables. An example is cited for demonstrating the feasibility and practicability of the proposed method, and results show that the ITL-TOPSIS is an effective decision-making tool for robot evaluation and selection with uncertain and incomplete information.     

An improved FMEA method based on the linguistic weighted geometric operator and fuzzy priority

Using the group linguistic information aggregation method, this research improved upon conventional failure mode and effect analysis (FMEA), which had the problems of the inevitable subjectivity of expert evaluations, and of the difficulty of determining the weights of experts' evaluations. First, this research treated the three risk factors of FMEA evaluation as linguistic variables and introduced a linguistic weighted geometric (LWG) operator to implement algebraic operations on the results of expert evaluations. This treatment overcame the disadvantage of fuzzy theory-based methods in which decision-making information could be lost due to the twice conversion process. Second, the weights of experts' evaluations were calculated based on the consistency of experts' ranking using a fuzzy priority method. This method placed a lower weight for the experts whose evaluation departed from group consensus, and therefore decreased the impact of the unfairness of experts on evaluation results. Finally, this article demonstrated the effectiveness and applicability of this method by an example of failure-mode analysis on the grinding wheel system of a numerical control machine.     

社会网络环境下融合概率语言和QUALIFLEX的 绿色包装评价方法

为科学合理地评价绿色包装方案,提出一种社会网络环境下,融合概率语言和QUALIFLEX的绿色包装评价方法。先确定绿色包装评价指标体系并利用概率语言术语集（PLTS）表达决策专家的评价信息;然后分别利用决策专家间信任关系网络和决策专家-准则偏好关系矩阵,计算决策专家与准则的权重;最后结合QUALIFLEX方法确定备选绿色包装方案的优序关系。通过与其他方法进行对比,验证了所提出方法的有效性和合理性。     

基于时间段决策视点的ERP供应商选择模型

结合ERP实施风险特点,从战略、战术和应用的时间段决策视点出发,把ERP软件供应商的选择风险划分为:长期合作风险、供应商服务风险、软件质量风险和供应商费用风险,建立了ERP软件供应商选择风险评价模型;通过调查问卷,运用因子分析方法进行实证分析;利用未确知测度提出了企业选择ERP软件供应商的评价方法.     

A Novel Approach for FMEA: Combination of Interval 2‐Tuple Linguistic Variables and Gray Relational Analysis

Failure mode and effect analysis (FMEA) is a powerful tool for defining, identifying, and eliminating potential failures from the system, design, process, or service before they reach the customer. Since its appearance, FMEA has been extensively used in a wide range of industries. However, the conventional risk priority number (RPN) method has been criticized for having a number of drawbacks. In addition, FMEA is a group decision behavior and generally performed by a cross‐functional team. Multiple experts tend to express their judgments on the failure modes by using multigranularity linguistic term sets, and there usually exists uncertain and incomplete assessment information. In this paper, we present a novel FMEA approach combining interval 2‐tuple linguistic variables with gray relational analysis to capture FMEA team members’ diversity opinions and improve the effectiveness of the traditional FMEA. An empirical example of a C‐arm X‐ray machine is given to illustrate the potential applications and benefits of the proposed approach. Copyright © 2014 John Wiley & Sons, Ltd.     

Global supplier selection: a fuzzy-AHP approach

Global supplier selection has a critical effect on the competitiveness of the entire supply chain network. Research results indicate that the supplier selection process appears to be the most significant variable in deciding the success of the supply chain. It helps in achieving high quality products at lower cost with higher customer satisfaction. Apart from the common criteria such as cost and quality, this paper also discusses some of the important decision variables which can play a critical role in case of the international sourcing. The importance of the political-economic situation, geographical location, infrastructure, financial background, performance history, risk factors, etc., have also been pointed out in particularly in the case of global supplier selection. Supplier selection problem related to the global sourcing is more complex than the general domestic sourcing and as a result it needs more critical analysis, which could not be found properly in past available literatures. This paper discusses the fuzzy based Analytic Hierarchy Process (fuzzy-AHP) to efficiently tackle both quantitative and qualitative decision factors involved in selection of global supplier in current business scenario. The fuzzy-AHP is an efficient tool to tackle the fuzziness of the data involved in deciding the preferences of the different decision variables involved in the process of global supplier selection. The triangular fuzzy numbers are used to transform the linguistic comparison of the different decision criteria, sub-criteria and performance of the alternative suppliers. The pairwise comparison matrices help in deciding the synthetic extent value of each comparison and finally, the priority weights of one alternative over another are decided in this paper. An example from a manufacturing industry searching for the global supplier for a critical component is used to demonstrate the effective implementation procedure of proposed fuzzy-AHP technique. The proposed model can provide the guidelines and directions for the decision makers to effectively select their global suppliers in the current competitive business scenario.     

融合社会网络和优序关系的绿色包装评价方法

在绿色包装方案选择时,针对准则数量显然超过方案数量且在社会网络环境下群体决策中,决策专家间信任关系及对准则的偏好关系复杂的特点,提出融合社会网络和优序关系的绿色包装评价方法。先确定绿色包装方案评价指标,并利用概率语言术语集表达决策专家的评价信息;然后利用社会关系网络计算决策专家权重,并利用偏好关系网络结合可能度公式计算准则权重;最后用QUALIFLEX方法确定备选绿色包装方案的优序关系。通过与其他方法进行对比,验证了所提方法的有效性和合理性。     

Evaluation,ranking and selection of R&D projects by multiple experts: an evidential reasoning rule based approach

As a typical multi-criteria group decision making (MCGDM) problem, research and development (R&D) project selection involves multiple decision criteria which are formulated by different frames of discernment, and multiple experts who are associated with different weights and reliabilities. The evidential reasoning (ER) rule is a rational and rigorous approach to deal with such MCGDM problems and can generate comprehensive distributed evaluation outcomes for each R&D project. In this paper, an ER rule based model taking into consideration experts’ weights and reliabilities is proposed for R&D project selection. In the proposed approach, a utility based information transformation technique is applied to handle qualitative evaluation criteria with different evaluation grades, and both adaptive weights of criteria and utilities assigned to evaluation grades are introduced to the ER rule based model. A nonlinear optimisation model is developed for the training of weights and utilities. A case study with the National Science Foundation of China is conducted to demonstrate how the proposed method can be used to support R&D project selection. Validation data show that the evaluation results become more reliable and consistent with reality by using the trained weights and utilities from historical data.     

An integrated weighted fuzzy multi-objective model for supplier selection and order scheduling in a supply chain

This paper presents a new weighted fuzzy multi-objective model to integrated supplier selection, order quantity allocation and customer order scheduling problem to prepare a responsive and order-oriented supply chain in a make-to-order manufacturing system. Total cost and quality of purchased parts as well as the reliability of on-time delivery of customer orders are regarded as the objectives of the model. On the other hand, flexible suppliers can contribute to the responsiveness and flexibility of entire supply chain in the face of uncertain customer orders. Therefore, a mathematical measure is developed for evaluating the volume flexibility of suppliers and is considered as the other objective of the model. Furthermore, by considering the effect of interdependencies between the selection criteria and to handle inconsistent and uncertain judgments, a fuzzy analytic network process method is used to identify top suppliers and consider as the last objective. In order to optimise these objectives, the decision-maker needs to decide from which supplier to purchase parts needed to assemble the customer orders, how to allocate the demand for parts between the selected suppliers, and how to schedule the customer orders for assembled products over the planning time horizon. Numerical examples are presented and computational analysis is reported.