A QFD-based fuzzy MCDM approach for supplier selection

Supplier selection is a highly important multi-criteria group decision making problem, which requires a trade-off between multiple criteria exhibiting vagueness and imprecision with the involvement of a group of experts. In this paper, a fuzzy multi-criteria group decision making approach that makes use of the quality function deployment (QFD) concept is developed for supplier selection process. The proposed methodology initially identifies the features that the purchased product should possess in order to satisfy the company’s needs, and then it seeks to establish the relevant supplier assessment criteria. Moreover, the proposed algorithm enables to consider the impacts of inner dependence among supplier assessment criteria. The upper and the lower bounds of the weights of supplier assessment criteria and ratings of suppliers are computed by using the fuzzy weighted average (FWA) method. The FWA method allows for the fusion of imprecise and subjective information expressed as linguistic variables or fuzzy numbers. The method produces less imprecise and more realistic overall desirability levels, and thus it rectifies the problem of loss of information. A fuzzy number ranking method that is based on area measurement is used to obtain the final ranking of suppliers. The computational procedure of the proposed framework is illustrated through a supplier selection problem reported in an earlier study.     

An integrated approach for supplier selection in multi-item/multi-supplier environment

One of the important stages in supply chain management which regards all the activities from the purchasing of raw material to final delivery of the product is the supplier selection process. Since it is the first stage of the supply chain management, it is a critical process affecting the consecutive stages. It is simply desired to select the best supplier for a specific product. But since there are a lot of criteria and alternatives to be considered, numerous decision making models have been proposed to provide a solution to this problem. Within this study, an integrated approach including fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and a mixed integer linear programming model is developed to select the best supplier in a multi-item/multi-supplier environment. The importance value of each supplier with respect to each product is obtained via fuzzy TOPSIS in the first stage. Then in the second stage, these values are used as an input in the mathematical model which determines the suppliers and the quantities of products to be provided from the related suppliers. So as to validate the proposed methodology, an application is performed in air filter sector.     

An integrated FANP–MOLP for supplier evaluation and order allocation

In the face of acute global competition, supplier management is rapidly emerging as a crucial issue to any companies striving for business success and sustainable development. To optimize competitive advantages, a company should incorporate “suppliers” as an essential part of its core competencies. Supplier evaluation, the first step in supplier management, is a complex multi-criteria decision-making (MCDM) problem, and its complexity is further aggravated if the highly important interdependence among the selection criteria is taken into consideration. The objective of this paper is to suggest a comprehensive decision method for identifying top suppliers by considering the effects of interdependence among the selection criteria, as well as to achieve optimal allocation of orders among the selected suppliers.     

Supplier selection by the pair of nondiscretionary factors-imprecise data envelopment analysis models

Discretionary models for evaluating the efficiency of suppliers assume that all criteria are discretionary, that is, controlled by the management of each supplier and varied at its discretion. These models do not assume supplier selection in the conditions that some factors are nondiscretionary. The objective of this paper is to propose a new pair of nondiscretionary factors-imprecise data envelopment analysis (NF-IDEA) models for selecting the best suppliers in the presence of nondiscretionary factors and imprecise data. A numerical example demonstrates the application of the proposed method.     

基于产品平台的多目标供应商预选方法研究

由于供应商选择问题直接影响着企业的最终收益, 所以它对企业来说一直是一个重要的决策问题. 在以往的研究中, 供应商选择仅仅是从产品零部件的角度去考虑而没有从产品的整体出发. 此外, 传统的供应商选择都是发生在产品设计阶段之后的产品生产阶段. 然而, 在产品设计初期考虑供应商选择问题可以有效地避免合适供应商的短缺问题. 提出了一个基于产品平台的多目标供应商预选方法, 并在产品设计初期从产品整体角度建立了一个以最小化产品族外包成本、最小化产品族生产风险以及最小化供应商供应时间为多目标的优化模型, 从而有助于决策者在产品开发的早期对产品整体设计方案进行改善. 此外, 由于产品平台存在部件共享问题, 因此在优化模型中也考虑了部件共享对供应商预选结果的影响. 采用非支配排序遗传算法(NSGA-II)对优化模型进行求解, 并通过实际案例来说明提出的优化方法以及求解算法的合理性和有效性.     

Application of fuzzy topsis for ranking suppliers of supply chain in automobile manufacturing companies in Iran

Evaluating, ranking and selecting of good supplier play an important role in decreasing of buying risk and increasing of efficiency and effectiveness in value chain and competitive ability of organizations. The goal of this paper is determination and localization of criteria, ranking and selecting suppliers in Automobile Manufacturing Companies in Iran. Based on literature review, 27 criteria were selected and localized, then using factor analysis, they were decreased to 6 items including quality, delivery, technical skill, after sales services, investment and product design. Ultimately, 4 suppliers including Tavan, Borna, Saba and Niroogostaran have been assessed and ranked by fuzzy topsis technique. The results of the research state that score of Borna is better than others with coefficient of 0.52, and from this view, Tavan, Saba and Niroogostaran are in the next ranking with coefficient of 0.45, 0.41, 0.31, respectively. Finally, it concludes some remarks including discussion, summary of implications for managers about how they can use this research results for selecting the best supplier and promoting the competitive ability of their organization, and directions for their further work too.     

Fuzzy measures of supplier evaluation under lean concepts

Supplier evaluation is a multiple attribute decision-making (MADM) problem involving a mixture of qualitative and quantitative attributes. Some mathematical programming techniques have difficulty in dealing with the qualitative attributes that are not easy to measure but very important in supplier evaluation. Fuzzy set theory is useful whenever variables defining a complex and vague system can neither be quantitatively defined nor assigned very precise measures, but are described by linguistic values. This paper presents a procedure for supplier evaluation by incorporating fuzzy set theory into the evaluation process to handle the qualitative attributes in the problem. A mathematical ranking method is used to convert the qualitative attributes into crisp scores. All the quantitative and qualitative performance measures are normalized and then using the proposed model, data are integrated into a single score to rank suppliers. The model application is demonstrated through two previously reported data sets under lean philosophy.     

基于中智犹豫模糊语言优先QUALIFLEX方法的绿色供应商选择

针对绿色供应商选择过程中,评价指标数量明显超过可供选择的供应商数量且指标之间存在优序关系等特点,提出了基于中智犹豫模糊语言优先QUALIFLEX方法的绿色供应商选择方法.首先,利用中智犹豫模糊语言表征评价信息和评价权重;其次,构造优先矩阵对指标权重做精确化处理,考虑到决策者对指标的要求和指标之间的优序关系,对指标权重进行修订;然后,提出改进的中智犹豫模糊语言余弦距离测度,在此基础上借助QUALIFLEX方法确定备选供应商的最终排序;最后,利用化学制药企业选择原料供应商的案例验证了所提方法的有效性.     

An interval type-2 fuzzy sets-based TODIM method and its application to green supplier selection

With the increasing awareness and significant environmental pressures from various stakeholders, companies have realized the significance of selecting green suppliers to their supply chain activities, which involves multiple criteria with uncertainty and the decision makers’ behaviour with irrational. Interval type-2 fuzzy sets (IT2 FSs) have advantages in modelling uncertainty over type-1 fuzzy sets. And TODIM is an useful non-linear prospect model for selecting the irrationally determined alternatives, but the ratings and weights are crisp values. In this paper, we develop the IT2 FSs-based TODIM method to select green supplier. First, we introduce a new distance computing method for IT2 FSs to assist the dominance models to deal with gains (losses) computation. Second, we identify the gains (losses) computing expression through comparing the ranking values of the IT2 FSs evaluations, and obtain the dominance degree of one alternative over others. Third, we use the presented IT2 FSs ranking method using possibility mean and variation coefficient concepts to defuzzify the dominance degree, and obtain the crisp global performance to select the best alternative. Finally, we also apply the proposed IT2 FSs-based TODIM method to green supplier selection for automobile manufacturers.     

竞争性供应商选择电商平台销售模式的互动机理研究

通过构建两个供应商和两个电商平台之间的博弈模型,探讨竞争性供应商选择电商平台销售模式的互动机理。研究发现:(1)竞争性供应商在电商平台销售模式选择上存在互动机理。(2)在短期均衡中,当佣金费率较高或较低时,供应商的销售模式选择不受竞争对手影响;当佣金费率适中时,供应商的销售模式选择将采取跟随策略,与竞争对手的选择保持一致。(3)在长期均衡中,当佣金费率较低时,两个供应商均会选择代销模式;当佣金费率较高时,两个供应商均会选择转销模式;当供应商自身的佣金费率较高(较低),竞争对手的佣金费率较低(较高)时,供应自身选择转销(代销)模式,竞争对手会选择代销(转销)模式。     

Evaluating and selecting the supplier in detergent production industry using hierarchical fuzzy TOPSIS

Supply chain management has increasingly attracted attention as a systematic approach to integrate the supply chain in order to planning and controlling the materials and information from suppliers to customers. One of the most important issues in supply chain management is selection of the appropriate supplier which has significant effect on purchasing cost decrease and increase in the organization’s competition ability. Selection of the best supplier is naturally complex with no definite structure, and dependent on the type of suppliers’ activity. In the process of decision making about suppliers and many qualitative and quantitative performance indicators such as quality, price, flexibility, and due date should be considered. Then, the supplier selection problem is a multi-criteria decision making problem where numerous methods have been proposed to solve this problem so far. In the current paper, four suppliers of imported raw material “Tripolyphosphate (TPP)” (primary material to produce the detergent powder with a case study in Iran) are evaluated based on 25 effective criteria using the hierarchical fuzzy TOPSIS (HFTOPSIS) approach.     

Vendor rating for an entrepreneur development programme: a case study using the analytic hierarchy process method

With collaborative purchasing programmes where one of the aims is to develop suppliers, vendor rating is important not only in supplier selection and in deciding how to allocate business but also to determine where scarce development effort is best applied. This paper describes a case study into vendor rating for a government sponsored Entrepreneur Development programme in Malaysia. The paper reviews current methods for vendor rating and finds them wanting. It illustrates a new approach based on the use of Saaty's Analytic Hierarchy process method, which was developed to assist in multi-criteria decision problems. The new method overcomes the difficulties associated with the categorical and simple linear weighted average criteria ranking methods. It provides a more systematic way of deriving the weights to be used and for scoring the performance of vendors.     

A decision model for supplier selection in the presence of dual-role factors

Best suppliers help manufacturers to gain and sustain a competitive advantage by improving product quality, reducing cost, shortening lead-time and so on. The crucial role played by suppliers in a supply chain renders the selection of a supplier or suppliers a significant work that attracts the attention of both researchers and practitioners. In the literature, data envelopment analysis (DEA) as a nonparametric technique is often applied to conduct a performance analysis. Little attention, however, has been paid to dual-role factors in the supplier selection process. This paper proposes a novel two-step approach to select suppliers in the presence of dual-role factors. As a combination of DEA and two-person zero-sum game theory, our work considers the strategic behaviour of the external environment and is able to handle the supplier selection in a competitive environment. Moreover, the proposed model circumvents the requirement to specify the status of a dual-role factor ahead of an evaluation and is easy to solve. Finally, the applicability of the procedure is illustrated by an application to a data set of 18 suppliers.     

Multisourcing suppliers selection in service outsourcing

Multisourcing suppliers selection in service outsourcing involves selecting a supplier portfolio with a reasonable number of suppliers and better performance to cover aspiration levels of criteria. It is a specific weighted matching problem with new challenges. This paper proposes a decision method for solving this problem. In the proposed method, different formats of preference information, including numerical values, interval numbers and linguistic variables, are used to express alternative ratings. The technique for order preference by similarity to ideal solution is extended to aggregate the three formats of preference information. A bi-objective 0–1 linear programming model using the aggregated information is built to select a desired supplier portfolio, in which the objectives of minimization of suppliers number and maximization of supplier performance are involved. To solve this model, we transform it into an equivalent, and then an exact multi-objective branch-and-bound algorithm is developed to obtain Pareto-optimal solutions. In addition, a real case of an insurance company is used to illustrate the applicability of the proposed method.     

An efficient and simple model for multiple criteria supplier selection problem

Simply looking for vendors offering the lowest prices is not “efficient sourcing” any more. Selection of suppliers is a multiple criteria decision. We propose a weighted linear program for the multi-criteria supplier selection problem. In addition to mathematical formulation, this paper studies a transformation technique which enables our proposed model to be solved without an optimizer. The model for multi-criteria supplier selection problem can be easily implemented with a spreadsheet package. The model can be widely applied to practical situations and does not require the user with any optimization background.     

An a posteriori decision support methodology for solving the multi-criteria supplier selection problem

This research presents a novel, state-of-the-art methodology for solving a multi-criteria supplier selection problem considering risk and sustainability. It combines multi-objective optimization with the analytic network process to take into account sustainability requirements of a supplier portfolio configuration. To integrate ‘risk’ into the supplier selection problem, we develop a multi-objective optimization model based on the investment portfolio theory introduced by Markowitz. The proposed model is a non-standard portfolio selection problem with four objectives: (1) minimizing the purchasing costs, (2) selecting the supplier portfolio with the highest logistics service, (3) minimizing the supply risk, and (4) ordering as much as possible from those suppliers with outstanding sustainability performance. The optimization model, which has three linear and one quadratic objective function, is solved by an algorithm that analytically computes a set of efficient solutions and provides graphical decision support through a visualization of the complete and exactly-computed Pareto front (a posteriori approach). The possibility of computing all Pareto-optimal supplier portfolios is beneficial for decision makers as they can compare all optimal solutions at once, identify the trade-offs between the criteria, and study how the different objectives of supplier portfolio configuration may be balanced to finally choose the composition that satisfies the purchasing company's strategy best. The approach has been applied to a real-world supplier portfolio configuration case to demonstrate its applicability and to analyze how the consideration of sustainability requirements may affect the traditional supplier selection and purchasing goals in a real-life setting.     

Web based casting supplier evaluation using analytical hierarchy process

Manufacturing companies are increasingly dependent on outsourcing to improve their competitive position. At the same time, the approach to supplier selection has dramatically changed from being price-driven to one based on overall capability of the supplier, very much in evidence in the automobile castings sector facing the challenge of mass customization. In this study, 18 criteria have been identified for casting supplier assessment and segregated in four groups—product development capability, manufacturing capability, quality capability, and cost and delivery. A systematic approach to evaluating casting quality suppliers has been developed using the analytical hierarchy process, which enables the combination of tangible and intangible criteria and checking the consistency of decision-making. The approach has been implemented in a prototype web-based system.     

Multi-criteria supplier segmentation using a fuzzy preference relations based AHP

One of the strategic activities of a firm is supplier segmentation, whereby a firm creates groups of suppliers to handle them differently. Existing literature provides several typologies of suppliers, each of which uses different dimensions/variables. In this paper, different typologies are combined by distinguishing two overarching dimensions, the capabilities and the willingness of suppliers to cooperate with a particular firm. These dimensions cover almost all the existing supplier segmentation criteria mentioned in existing literature. For each particular situation, these dimensions can be specified using a multi-criteria decision-making method. A methodology is proposed that includes a fuzzy Analytic Hierarchy Process (AHP) which uses fuzzy preference relations to incorporate the ambiguities and uncertainties that usually exist in human judgment. The proposed methodology is used to segment the suppliers of a broiler company. The result is a segmentation of suppliers based on two aggregated dimensions. Finally some strategies to handle different segments are discussed and concluding remarks and suggestions for future research are provided.     

基于微博客的手机供应商排名推荐

微博作为一种新兴的日渐被广泛使用的网络平台,大大的满足了人们人际交流、信息获取等多方面的需求,它已经成为人们日常生活的重要组成部分.传统的供应商选择问题是从供应商角度出发,通过考虑成本等问题而得到解决的.借助新兴的网络平台-微博,利用微博数据的评价性信息,引入微博影响力评价的概念,提出了全新的供应商排名推荐方法,最终得出了基.于微博影响力评价的手机供应商排名.     

Reducing Inventory Costs and Choosing Suppliers with Order Splitting

Splitting orders among several suppliers is a common business practice. Two earlier studies pointed out that, when splitting an order between two suppliers, the major benefit in inventory-related costs is in the reduction of stockouts due to the reduction of the effective lead time and the effective lead time demand. This conclusion implies that, among several suppliers, one should select the two suppliers with the lowest average lead times. In contrast, our study shows that: (i) an important benefit is in the reduction of average inventory; (ii) this benefit can only be realized when one selects a second supplier with a ‘suitably’ larger average lead time than the first supplier - a strategy that contradicts the selection rule implied by the earlier studies. Therefore, there is an economic trade off between this benefit and the more well-known benefit of lower lead time demand achieved by using suppliers with the lowest average lead times.