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.     

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 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.     

First- and second-price sealed-bid auctions applied to push and pull supply contracts

We investigate a newsvendor-type retailer sourcing problem under demand uncertainty who has the option to source from multiple suppliers. The suppliers’ manufacturing costs are private information. A widely used mechanism to find the least costly supplier under asymmetric information is to use a sealed-bid reverse auction. We compare the combinations of different simple auction formats (first- and second-price) and risk sharing supply contracts (push and pull) under full contract compliance, both for risk-neutral and risk-averse retailer and suppliers. We show the superiority of a first-price push auction for a risk-neutral retailer. However, only the pull contracts lead to supply chain coordination. If the retailer is sufficiently risk-averse, the pull is preferred over the push contract. If suppliers are risk-averse, the first-price push auction remains the choice for the retailer. Numerical examples illustrate the allocation of benefits between the retailer and the (winning) supplier for different number of bidders, demand uncertainty, cost uncertainty, and degree of risk-aversion.     

图书馆图书供应商选择的PROMETHEE/TOPSIS决策模型

图书供应商选择对图书馆各项功能的实现和未来的发展有着重要影响,这一重要问题的解决方法受到很多学者的关注。在构建图书供应商评价指标体系的基础上,提出了一种供应商选择的PROMETHEE／TOPSIS决策模型。模型通过向具有完全补偿性的TOPSIS方法中引入偏好函数,并结合摆动赋权方法,减少了决策信息的损失和扭曲,更好地反映了图书供应商间的差别。最后通过实例证明了该模型的有效性和实用性。     

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.     

基于二维二元语义和模糊AHP-TODIM的低碳供应商选择方法

针对专家给出二维语言评价信息的低碳供应商评选问题,提出一种基于二维二元语义和模糊AHP-TODIM的方法。该方法首先提出改进的二元语义模型,基于此定义二维二元语义及其加权平均算子。接着构建低碳供应商评价的指标体系。最后,将专家给出的二维语言评价信息转化为二维二元语义,使用模糊AHP法计算指标权重,并利用二维二元语义加权平均算子集结信息,在此基础上将TODIM方法扩展到二维二元语义环境以获取低碳供应商排序。案例分析说明了所提出的方法的有效性。     

Supplier selection and order allocation problem using a two-phase fuzzy multi-objective linear programming

The aim of this paper is to solve a supplier selection problem under multi-price level and multi-product using interactive two-phase fuzzy multi-objective linear programming (FMOLP) model. The proposed model attempts to simultaneously minimize total purchasing and ordering costs, a number of defective units, and late delivered units ordered from suppliers. The piecewise linear membership functions are applied to represent the decision maker’s fuzzy goals for the supplier selection and order allocation problem, and can be resulted in more flexibility via an interactive decision-making process. To demonstrate effectiveness of the proposed model, results of applying the proposed model are shown by a numerical example. The analytical results show that the proposed approach is effective in uncertain environments and provide a reliable decision tool for integrated multi-objective supplier selection problems.     

Production control and replenishment strategy with multiple suppliers

This paper considers the joint supplier selection, replenishment and manufacturing control problem in a dynamic stochastic context. This problem is characterized by conflicting interests between suppliers, the manufacturer, and clients, which raise the need for coordination and information sharing. This paper contributes to the discourse mainly by developing and resolving an integrated mathematical model leading to information sharing strategies for supplier selection, replenishments and production activities. This is an optimal control problem with state constraints and hybrid dynamics. A dynamic stochastic model is thus proposed, and the optimality conditions obtained are then solved numerically. It is shown that the problem considered leads to a modified state-dependent multi-level (s, S) policy for the supplier selection and replenishment strategy and a base-stock policy for the production activities. The fact that these control policies are coupled confirms the necessity of considering the interactions present in the system in an integrated model. The obtained results show clearly that it is always profitable to consider multiple suppliers to make replenishment and production decisions. Moreover, it is shown that the availability rates of the supply chain actors and the replenishment lead time are important parameters to consider when choosing the best supplier.     

Supplier selection using axiomatic fuzzy set and TOPSIS methodology in supply chain management

The current paper presents a comprehensive methodology for supplier selection. In the first stage, the linguistic values expressed as trapezoidal fuzzy numbers are used to assess the weights of the criteria. The Axiomatic Fuzzy Set clustering (AFS) method, which handles ambiguity and fuzziness in the supplier selection problem effectively, is applied to cluster the suppliers and evaluate each potential supplier that aims at obtaining initial supplier ranking. In the second stage, the Fuzzy Analytic Hierarchy Process (FAHP) model is constructed to determine the weight of various quantitative and qualitative criteria. To address multiple decision criteria in supplier ranking, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed to select the final suppliers. A numerical example composed of 30 suppliers and 6 criteria is studied, and the experimental results show that the proposed evaluation framework is suitable for supplier selection decisions even with the dependent criteria/attributes.     

基于概率语言术语集改进TODIM法的应急物流供应商评价研究

为了科学合理地评价应急物流供应商,提出了一种基于概论语言术语集改进TODIM法的评价方法。针对应急物流的特点,从快速响应时间、物资质量、成本控制、企业服务和企业内外部条件五个维度,构建应急物流供应商评价指标体系;在此基础上,为充分反映专家的偏好和评价信息,将概率语言术语集与TODIM方法相结合,构建基于改进TODIM方法的评价模型,对应急物流供应商进行评价;最后,通过实例分析验证该方法的可行性与有效性。     

不确定偏好序信息下考虑主体心理行为的双边匹配决策方法

针对基于不确定偏好序信息的双边匹配问题,本文提出了一种决策方法。给出了双边匹配和不确定偏好序的相关概念,同时给出了不确定偏好序信息下考虑主体心理行为的双边匹配问题描述;以每个主体给出的临界值作为其参照点,计算了每个主体给出的不确定偏好序相对于参照点的收益或损失;考虑到主体损失规避的心理行为特征,依据TODIM思想计算每个主体对另一方主体的益损值的感知价值;在此基础上,构建了求解该双边匹配问题的双目标优化模型,使用线性加权法将双目标优化模型转化为单目标优化模型,通过求解该单目标优化模型获得匹配结果;最后,通过IT服务外包中的供给方与需求方的双边匹配实例分析说明了所提方法的有效性。     

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.     

An exact algorithm for the Capacitated Total Quantity Discount Problem

In this paper we analyze the procurement problem of a company that needs to purchase a number of products from a set of suppliers to satisfy demand. The suppliers offer total quantity discounts and the company aims at selecting a set of suppliers so to satisfy product demand at minimum purchasing cost. The problem, known as Total Quantity Discount Problem (TQDP), is strongly NP-hard. We study different families of valid inequalities and provide a branch-and-cut approach to solve the capacitated variant of the problem (Capacitated TQDP) where the quantity available for a product from a supplier is limited. A hybrid algorithm, called HELP (Heuristic Enhancement from LP), is used to provide an initial feasible solution to the exact approach. HELP exploits information provided by the continuous relaxation problem to construct neighborhoods optimally searched through the solution of mixed integer subproblems. A streamlined version of the proposed exact method can optimally solve in a reasonable amount of time instances with up to 100 suppliers and 500 products, and largely outperforms an existing approach available in the literature and CPLEX 12.2 that frequently runs out of memory before completing the search.     

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.     

Hybrid Multi-attribute Decision Making Method of Electric Coal Procurement in Industry

Electric coal procurement is the basis of electric power production. In this paper, the problem of supplier selection is studied in multi-source procurement of electric coal. Concretely, the index system of supplier selection is presented, including the evaluation attributes of price, quantity, quality, delivery time and the reputation of supplier. Then, the problem of supplier selection is converted into a problem of hybrid multi-attribute decision making, and a projection method based on hybrid technique for order preference by similarity to ideal solution (TOPSIS) is presented to rank all suppliers and select winners. Its decision example is also given to implement the presented decision method and to demonstrate its effectiveness and practicality. This paper gives an effective way to the hybrid multi-attribute decision making for multi-source procurement of electric coal under fuzzy uncertain environment.     

A practical expected-value-approach model to assess the relevant procurement costs

As an improvement to a series of expected value approach models, this study presents a supplier portfolio decision model, rather than a number of suppliers decision model. The model assesses risks as costs, considers types of heterogeneity in a procurement process and links the assessed terms in the programming model with accounting concepts. The model is then confirmed by using a procurement decision case with real data. The analysis has several implications for modelling, application and practice. In the light of the counterexamples shown, some thoughts pertaining to procurement decisions in supply management are reconsidered.     

基于改进支持向量机的高端装备制造业供应商分类研究

针对现有供应商分类方法应用于高端装备制造业供应商所存在的局限性,从相互依赖视角构建了高端装备制造业供应商分类指标体系,提出了基于改进支持向量机的高端装备制造业供应商分类模型。该模型根据供应商误分代价不同,设计代价敏感支持向量机分类器,利用粒子群算法优化分类器的参数,并采用概率输出方法对多个优化的二类分类器的结果进行组合以实现多类分类。实验结果表明,该模型提高了现有方法的分类效果,可以降低总体误分代价,有效识别出对高端装备制造企业具有重大影响的供应商,为高端装备制造企业实施供应商分类管理提供了依据。     

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.