基于模糊决策的供应商选择方法

在分析建立供应商评价指标体系所应遵循的三大原则的基础上，提出了一套供应商评价指标体系。由于供应商选择问题中包含大量的不确定和模糊因素，为此将模糊集合论的思想和方法引入供应商评价中，建立了供应商模糊评价模型，最后给出实例予以验证。     

既有供应商模糊综合评价

对既有供应商的评价是供应链管理的重要内容之一。通过对选择供应商与既有供应商的评价进行比较分析,从生产制造实力、产品质量水平、质量保证能力、工程技术能力、协同能力等5个方面建立了既有供应商的评价指标体系与二级模糊综合评价模型。实证研究表明所构建的评价指标体系与评价模型能够对既有供应商的优劣做出正确的评价,为既有供应商的评价提供了科学的方法。     

产品生命周期过程(横向集成)供应商选择模型研究

通过分析集成化供应链管理环境下供应商选择过程,给出了选择指标体系及选择步骤。在此基础上,建立了“横向”集成型企业供应商选择的模糊综合评价选择模型。应用此模型可对选择最满意的供应商做出相应的决策。     

模糊综合评价在质量工具选择中的应用

针对目前企业进行质量工具选择时出现的问题,在分析其特点的基础上,提出了利用模糊综合评价方法的解决方案,建立了工具选择的评价指标体系,详细阐述了该方法的算法步骤,最后以某制造企业为例进行了实例验证.结果表明,应用模糊综合评价法可以充分保证工具选择的准确性和科学性.     

基于犹豫模糊广义Choquet积分的风险型供应商选择方法

针对传统供应商选择方法没有考虑市场风险因素以及决策者风险态度的问题,提出了一种基于TODIM的风险型供应商选择方法。针对模糊集处理评价信息的不足,采用犹豫模糊数处理决策者给出的供应商评价值,可以有效反映决策者的不同意见和犹豫性。采用犹豫模糊测度的广义Choquet积分对指标间的相互影响关系进行分析,计算指标权重。考虑到决策者的风险态度,采用改进的TODIM方法对决策者进行心理偏好分析并对各候选供应商进行排序。最后以某生鲜企业选择生鲜候选供应商为例,验证了所提方法的有效性。     

企业的场址选择及评价模型

运用模糊数学的原理方法，根据企业的特点，给出了场址选择评价因素指标体系，建立了场址选择的二级模糊综合评价模型，采用层次分析法(AHP)对备选场址进行选择。     

基于供应链管理的供应商选择问题初探

首先讨论了供应链环境下选择供应商的意义，然后建立了供应商选择的评价指标体系，重点讨论了应用TOPSIS 方法对供应商选择的模型及算法，最后用一个简单的案例进行了说明。     

基于“TOPSIS／DEA／AHP”模型的战略性供应商选择

研究了供应链环境下战略性供应商选择的问题.通过分析和总结供应商评价选择的准则、指标和方法,以供应链核心企业选择战略性供应商为目标,提出了战略性供应商评价的指标体系,利用整体DEA有效模型来反映供应商的绩效,利用AHP反映供应链核心企业选择供应商的主观愿望,从而构建了TOPSIS与整体DEA有效相结合的"TOPSIS/DEA/AHP"战略性供应商评价选择模型,并通过实证分析,证实了该模型及方法的可行性.     

基于AHP和熵值法的项目供应商灰色关联评价

结合企业实际应用需求,基于项目管理的理念构建了半导体制造扩建项目系统设备供应商综合评价指标体系,提出了AHP与熵值法组合赋权的供应商灰色关联综合评价方法,结合企业实际项目案例进行了应用,验证了指标体系和评价方法的有效性.     

TOPSIS法在材料供应商优选中的应用

结合某建设工程项目中混凝土管桩供应商优选的实际情况，提出了材料供应商选择的指标体系，建立了基于熵权的逼近理想解的排序方法（TOPSIS）的评价模型，由于在该方法中采用了熵权，避免了多因素权重确定的主观性。最后，通过实例对该方法的应用进行说明。     

An application of the fuzzy ELECTRE method for supplier selection

Supplier selection is vital to the success of a manufacturing firm. Supplier selection is a multi-criteria decision-making problem and is of strategic importance for most companies. As the conventional methods for supplier selection are inadequate for dealing with the imprecise or vague nature of linguistic assessment, a new method called the fuzzy technique for ELECTRE (ELimination Et Choix Traduisant la REalité) is proposed. The aim of this study is to compare and contrast crisp and fuzzy ELECTRE methods for supplier selection. The proposed methods are applied to a manufacturing company in Turkey. After determining the criteria that affect the supplier selection decisions, the results for both crisp and fuzzy ELECTRE methods are presented.     

Procedure for supplier selection based on Cpm applied to super twisted nematic liquid crystal display processes

The loss-based process capability index C _pm , sometimes called the Taguchi index, has been proposed to the manufacturing industry as a method to measure process performance. The index C _pm takes into account the targeting degree of the process, which essentially measures process performance based on average process loss. Based on the C _pm index, a mathematically complicated approximation method was developed previously for selecting a subset of processes containing the best supplier from a given set of processes. The present paper implements this method and develops a practical step-by-step procedure to aid supplier selection decisions. The accuracy of the selection method is investigated using a simulation technique. The accuracy study provides useful information about the sample size required for a designated selection power. A two-phase selection procedure is developed to select a better supplier and to examine the magnitude of the difference between the two suppliers. Also investigated is a real-world case on the super twisted nematic liquid crystal display manufacturing process, and it is applied to the selection procedure using actual data collected from the factories to reach a decision in supplier selection.     

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.     

Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic

As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.     

Design of an integrated supplier selection and multi-echelon distribution inventory model in a built-to-order supply chain environment

The paper deals with the development of an integrated supplier selection and multi-echelon distribution inventory model (MEDIM) for the original equipment manufacturing company in a built-to-order supply chain environment using fuzzy analytical hierarchy process (FAHP) and a genetic algorithm. The main objective is to design the integrated qualitative decision-making of the supplier selection model using FAHP with that of the quantitative mathematical model for the distribution inventory supply chain using a genetic algorithm to the built-to-order environment. The proposed model is validated by considering the case study in a tyre industry in Southern India. The software used for programming is C++ language.     

Designing of fuzzy expert heuristic models with cost management toward coordinating AHP,fuzzy TOPSIS and FIS approaches

In genuine industrial case, problems are inescapable and pose enormous challenges to incorporate accurate sustainability factors into supplier selection. In this present study, three different primarily based multi-criteria decision making fuzzy models have been compared with their deterministic version so as to resolve fuzzy prioritization problems. The developed model applies AHP, TOPSIS and fuzzy inference system (FIS) using a MATLAB toolbox to effectively analyze the interdependencies between sustainability criteria and select the best sustainable supplier in the fuzzy environment, while capturing all objective criteria. A typical supplier A4 has been awarded the most suitable supplier with 0.386 composite relative weights of AHP, relative closeness to ideal solution 0.7154 and normalized score index 0.219 FIS model using MATLAB toolbox.     

Integrated model for supplier selection and negotiation in a make-to-order environment

The paper deals with the development of an integrated supplier selection and negotiation process for multiple parts/materials procurement. The main objective is to integrate decisions in the internal supply chain of a make-to-order manufacturer. Two main decisions during the negotiation process are considered: (1) the manufacturing planning decision responsible for determining the production schedule and fabrication lot size and (2) the supplier selection decision concerning which suppliers are selected for company business and the order volume allocated to each selected supplier. The model is designed to support the negotiation process by generating a set of effective alternatives in each negotiation period. Its structure is multi-objective and non-linear. The combination of the interactive weighted Tchebycheff method and Benders decomposition method is applied to generate a set of effective alternatives to support the decision-maker in each negotiation period.     

Bootstrap approach for supplier selection based on production yield

Current manufacturing industries have increased their level of out-sourcing and relied more heavily on their supply chain as a source of competitive advantage. Supplier selection decisions have become an important component of production management. Those decisions have a significant impact on a firm's marketing competition, and suppliers may account for a large portion of the production cost. Production quality is one of the key factors in supplier evaluation. The manual of supplier certification includes a discussion of process capability analysis, which recommends a procedure for evaluating the most prevalent process capability index C _pk. However, the recommended procedure is applicable only when evaluating an individual supplier's performance. In this paper, we apply the bootstrap method to the supplier selection problem. We construct lower confidence intervals for the capability difference and ratio between two given suppliers. Performance comparisons are made among various bootstrap methods in terms of error probability and selection power. For convenience of applications, the sample sizes required for various designated selection power are also tabulated.     

A fuzzy AHP evaluation model for buyer–supplier relationships with the consideration of benefits,opportunities, costs and risks

With increasingly fierce global competition, firms in various industries need to build a cooperative buyer–supplier relationship to survive and to acquire reasonable profit. Even though the literature on various types of collaboration between firms is abundant and the works on supplier selection models are numerous, the research that provides a mathematical model for the selection of the most appropriate form of buyer–supplier relationship is very limited. Existing buyer–supplier evaluation models usually only consider the benefits from the relationship, but not the opportunities, costs and risks that may need to be confronted. The main objective of this study is to propose an analytical approach to evaluate the forms of buyer–supplier relationship between a manufacturer and its supplier. A fuzzy analytic hierarchy process (AHP) model, which applies fuzzy set theory and the benefits, opportunities, costs and risks (BOCR) concept, is constructed to deal with uncertainty and to consider various aspects of alternatives. Multiple factors that affect the success of the relationship are analysed by incorporating experts’ opinions on their priority of importance, and a performance ranking of the buyer–supplier forms is obtained. A case study of selecting the most appropriate buyer–supplier form between a TFT-LCD manufacturer and its colour filter supplier is presented, and the proposed model is applied to facilitate the decision process. The proposed model is a general form that can be tailored and applied by firms that are making decisions on buyer–supplier relationship.