Restricting weights in supplier selection decisions in the presence of dual-role factors

One of the uses of data envelopment analysis (DEA) is supplier selection. Weight restrictions allow for the integration of managerial preferences in terms of relative importance levels of various inputs and outputs. As well, in some situations there is a strong argument for permitting certain factors to simultaneously play the role of both inputs and outputs. The objective of this paper is to propose a method for selecting the best suppliers in the presence of weight restrictions and dual-role factors. This paper depicts the supplier selection process through a DEA model, while allowing for the incorporation of decision maker’s preferences and considers multiple factors which simultaneously play both input and output roles. The proposed model does not demand exact weights from the decision maker. This paper presents a robust model to solve the multiple-criteria problem. A numerical example demonstrates the application of the proposed method.     

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。     

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.     

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.     

基于粗糙集-层次分析法的制造业供应商评价选择

制造企业在确定供应商过程中,必须对供应商进行评价和选择,由于制造业的加工设备和加工工艺的复杂性,同时要确保供应商供货稳定和质量保证等多方面的因素,其评价指标体系必然有别于其它行业的评价指标.采用粗糙集属性约简的方法,对供应商评价选择指标进行约简分析,运用层次分析法对供应商进行评价选择.     

Suppliers selection in the presence of both cardinal and ordinal data

Traditionally, supplier selection models are based on cardinal data with less emphasis on ordinal data. However, with the widespread use of manufacturing philosophies such as just-in-time (JIT), emphasis has shifted to the simultaneous consideration of cardinal and ordinal data in supplier selection process. To select the best suppliers in the presence of both cardinal and ordinal data, this paper proposes an innovative method, which is based on imprecise data envelopment analysis (IDEA). A numerical example demonstrates the application of the proposed method.     

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.     

采购量分配决策模糊规划模型

供应商对形成企业的竞争力起着关键性的作用。采购决策中,采购商需要决策两方面的问题:应该选择哪些供应商以及在每一供应商应该采购多少。本文考虑了多目标性和目标的模糊性,同时为供应商选择和采购量分配提出了一个集成的决策模型。最后,通过一个算例阐释了该模型。     

Potential use of FP-growth algorithm for identifying competitive suppliers in SCM

The rapid development of global economy and the resulting increase in competition have prompted attention to be focused on supply chain management (SCM) for improved competitiveness. Supplier selection for reducing supplier base is an important goal in SCM. This paper aims at contributing an effective method that combines an FP-growth algorithm with set theory to identify the primary and secondary suppliers. An example of the proposed method to find key suppliers is presented, and the results show the proposed method to be effective.     

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.     

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.     

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.     

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.     

基于距离测度及支持度的混合评价信息供应商选择决策

新零售模式的推进迫使企业不断加强供应链节点上的供应商选择优化,是企业新时代发展面临的新课题。针对供应商选择优化提出一种基于距离测度及支持度的群决策方法,根据不同类型属性评价信息的距离测度定义,得到不同决策者之间关于单一属性指标的相互支持度,从而确定单个供应商各属性的群体综合评价值,并采用灰关联法对备选供应商进行排序择优。     

Using a DEA-cross efficiency approach in public procurement tenders

The paper addresses the topic of supplier selection in public procurement. According to European directives, when tenders are awarded through the “Most Economically Advantageous Tender” (MEAT) criterion, the awarding committee has to decide the tender evaluation criteria of the presented bids in advance. The authors propose a decision making tool that is aimed at helping the awarding committee in this difficult task and, at the same time, maintaining a transparent procedure in accordance with governmental procurement regulations and requirements as well as guaranteeing fair and equal evaluation of all bids. In this regard, the decision problem of supplier selection is addressed by applying an extension of the DEA (data envelopment analysis) methodology. The cross-efficiency evaluation is used for selecting the best supplier among the eligible candidates. The proposed technique allows the evaluation of quantitative data related to vendor selection and keeps the transparency features requested by public procurement. In addition, all bids are equally assessed according to the same objectively defined weights without any subjective setting by the public officers. The effectiveness and efficiency of the approach is supported by a case study that pertains to the tender of an Italian public agency.     

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.     

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.     

Designing an efficient supply chain network with uncertain data: a robust optimization—data envelopment analysis approach

Designing a supply chain network (SCN) is an important issue for organizations in competitive markets. In this paper, a novel robust SCN that considers the efficiencies and costs simultaneously is proposed. In order to estimate the efficiency of the producers and distributors, data envelopment analysis (DEA) model is incorporated into SCN. Moreover, to handle the uncertainty in data, a scenario-based robust optimization approach is applied. The proposed model finds out the efficient location of producers and distributors and determines the amount of purchases from each supplier in uncertain conditions. To illustrate the application of the proposed model, a numerical example is solved and results are analyzed.     

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.     

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.