基于熵权和TOPSIS法对工程材料供应商选择的评价研究

从产品质量、财务信用、产品价格、交货准时性、供应能力、地理位置6个维度创造性地构建工程材料供应商选择的指标体系,并在利用熵权法确定指标权重的基础上,应用TOPSIS法探讨综合选择工程材料供应商的最佳方案,最后举一算例进行验证。     

基于熵组合权和TOPSIS法相结合的连锁超市生鲜商品供应商选择

在连锁超市的经营过程中,供应商的选择直接影响着连锁超市的经营效益,通过对供应商的评价,选择适合企业发展的供应商有着极为重要的现实意义。本文以连锁超市生鲜商品的供应商评价与选择为例,构建出专门针对连锁超市生鲜食品供应商评价与选择指标体系。     

基于熵的改进TOPSIS法在业务外包供应商选择中的应用

影响3PL选择的因素很多．其中交货提前期（T）、产品质量（Q）、变货可靠度（R）和产品价格（P）等4个因素是3PL选择的关键因素。本文就从这4个关键因素着手，从现代供应链管理要讲究战略的角度出发．引进基于熵的改进TOPSIS法，选择合适的3PL．和企业建立起长期的合作伙伴关系。     

基于TOPSIS模型的火力发电企业电煤供应商选择评价研究

针对火力发电企业电煤供应商的特点,从成本因素、质量因素、到货因素三个方面,建立了由入厂标准煤单价、收到基恒容低位发热量、空气干燥基灰分、全水分、全硫、合格率、准时交货率、实收重量率8个指标构成的指标体系。采用了层次分析法确定的主观权重、熵权法确定客观权重,得到主观权重和客观权重相结合的组合权重,并使用TOPSIS模型对某火力发电企业的19个电煤供应商做出了评价和选择,对电煤供应商怎样提高竞争力以及火力发电企业对电煤供应商进行管理的重点内容提出了建议。     

基于熵权的灰色关联度分析方法在汽车零部件供应商选择中的应用

供应商选择是供应链运行的基础,运用单一的评价方法存在主观性过强的缺陷。为避免供应商选择单一评价方法出现不足,提出了基于熵权的灰色关联度分析评价方法,该方法综合运用信息熵权和灰色关联度分析方法的长处使供应商评价选择更客观合理。并以某汽车企业供应商选择为例进行了实证研究,表明这种方法应用于汽车零部件供应商选择简便可行。     

基于模糊TOPSIS方法的绿色供应商评价与选择

首先根据相关原则设计了一套新的、更加细致严谨的绿色供应商评价指标体系;指出已有的供应商评价方法的不足,应用了一种新的、更加精确合理的基于α水平截集的模糊TOPSIS方法来进行绿色供应商的评价与选择;最后进行算例分析,证实了方法的可行性及有效性。     

基于三角模糊数的供应商选择方法研究

为了较为客观科学地选择与评价供应商,将定性与定量指标数据统一量化,将层次分析法和三角模糊数相结合,构建了基于三角模糊数的供应商选择综合评价模型,并运用该模型以轨道交通企业为例进行了实证分析.该模型较好地解决了既有定性指标又有定量指标的指标体系评价问题,同时,在定量指标的隶属度确定方面更为客观.     

基于区间直觉模糊集TOPSIS法的供应商选择

供应商的选择一直是供应链管理的核心和关键,直接影响着整条供应链的运营。文章首先介绍了供应商选择的研究现状,在此基础上构建了供应商选择的评价指标体系,并引入直觉模糊集TOPSIS法进行供应商的选择。最后用一个实例阐述该指标体系和方法的应用,为供应商的选择提供了一种新的方法。     

风电制造企业物流供应商的选择研究——基于熵权的模糊综合评价法

通过分析风电设备制造企业物流的特点,建立了物流供应商评价指标体系.利用基于熵权的模糊综合评价模型对物流供应商进行评价选择.     

汽车零部件供应商选择方法应用研究

零部件采购是汽车制造企业供应链管理的重要环节,而供应商的选择是供应链管理的基础。文中将多属性决策理论中的改进TOPSIS法和熵值法的评价优势相结合,引入到汽车零部件供应商选择中来,并以具体的案例说明基于熵值法的改进TOPSIS法是一个可靠、有效且可以持续改善的汽车零部件供应商评价模型,为企业进行供应商选择、管理、监督、改善等活动提供更为有力的依据。     

A fuzzy-QFD approach to supplier selection

This article suggests a new method that transfers the house of quality (HOQ) approach typical of quality function deployment (QFD) problems to the supplier selection process. To test its efficacy, the method is applied to a supplier selection process for a medium-to-large industry that manufactures complete clutch couplings.The study starts by identifying the features that the purchased product should have (internal variables “WHAT”) in order to satisfy the company's needs, then it seeks to establish the relevant supplier assessment criteria (external variables “HOW”) in order to come up with a final ranking based on the fuzzy suitability index (FSI). The whole procedure was implemented using fuzzy numbers; the application of a fuzzy algorithm allowed the company to define by means of linguistic variables the relative importance of the “WHAT”, the “HOW”–“WHAT” correlation scores, the resulting weights of the “HOW” and the impact of each potential supplier.Special attention is paid to the various subjective assessments in the HOQ process, and symmetrical triangular fuzzy numbers are suggested to capture the vagueness in people's verbal assessments.     

A novel option contract integrated with supplier selection and inventory prepositioning for humanitarian relief supply chains

This paper proposes a novel two-period option contract integrated with supplier selection and inventory prepositioning. A two-stage scenario-based mixed possibilistic-stochastic programming model is developed to cope with various uncertainties. The first stage's decisions include supplier selection and capacity reservation level at each supplier/period and the level of inventory prepositioning. Furthermore, decisions regarding the time and exercised amount are made in the second stage. Applicability of the model is validated through a real case study. Finally, several sensitivity analyses are conducted to examine the effect of important parameters on the solutions to gain useful managerial insights.     

A novel hybrid multi-criteria method for supplier selection among SMEs on the basis of innovation ability

Today, small and large business houses operate collaboratively for the efficiency in the functioning of supply chains. Larger organisations mostly depend on small companies to supply majority of its components and thus they need to be careful while selecting their suppliers. Small organisations performing innovatively and supplying technologically upgraded as well as quality products at a cheaper rate can be a boon for the larger enterprise. This study develops a model for evaluating and selecting small firms as suppliers on the basis of their innovativeness. Best–Worst multi-criteria method is used to rank criteria of innovativeness and also to calculate their weights on the basis of expert opinion. Fuzzy TOPSIS methodology is used to rank the suppliers with respect to these criteria and finally select the best supplier among the available alternatives. A real-world application is illustrated by taking a case of auto component manufacturer and its seven suppliers, 5 main criteria and 23 sub-criteria are taken up for the study.

Abbreviations: AHP: analytical hierarchal process; ANP: analytical network process; DEMATEL: decision-making trail and evaluation laboratory; EMS: environment management system; ELECTRE: ELimination Et Choix Traduisant la REalité (elimination and choice expressing reality); FPIS: fuzzy positive ideal solution; FNIS: fuzzy negative ideal solution; ISM: interpretative structural modelling; PROMTHEE: preference ranking organisation method for enrichment evaluation; SME: small and medium enterprises; TOPSIS: technique for order preference by similarity to ideal solution; QFD: quality function deployment; VIKOR: VlseKriterijuska Optimizacija I Komoromisno Resenje; SP1; SP2; SP3; SP4; SP5; SP6; SP7: Various suppliers used as alternatives     

Exploring the circular economy paradigm: A natural resource-based view on supplier selection criteria

The paradigm of circular economy and the transfer of its principles to supply chain management has recently received much attention from researchers and practitioners. Limited natural resources, governmental legislation, and social responsibility for environmental preservation are the main factors for the development of circular supply chains. Especially in the automotive industry, critical materials are used to produce electric vehicles, reinforcing the importance of circularity for the industry. As the first stage of the supply chain, suppliers have a considerable influence on creating self-sufficient production systems, and in the automotive sector, a low level of vertical integration is important. Therefore, selecting suppliers is an enabler for circular supply chains, but this decision is a complex process due to multiple, partly conflicting criteria. To contribute to the knowledge in this research area, this study applies a fuzzy decision-making trial and evaluation laboratory approach for supplier selection in a circular supply chain in a case study of electric vehicles. First, a set of criteria for supplier selection in circular supply chains was identified based on a literature review and was systematically categorized based on the natural resource-based view. Afterward, the criteria were assessed and refined by experts with a strong procurement background in the automotive industry. Second, the experts were interviewed for value collection, and finally, the mutual influence of the criteria was determined. The results show that the most important criteria for circular supplier selection in electric vehicle supply chains are environmental standards, environmental-related certifications, resource consumption, and waste generation. Regarding the natural resource-based view, short-term focused criteria addressing the capability of pollution prevention have a higher importance compared to long-term criteria that drive sustainable development. In addition, this study classifies the criteria into the categories of causes and effects, discusses the prominence of the criteria, and presents a strategic map showing the mutual influences of the criteria. The results contribute to the theoretical and practical discussion on circular supply chains by identifying the key criteria for circular supplier selection and providing decision-making support for procurement managers.     

Application of an integrated decision support process for supplier selection

In many firms the value of purchased materials and components accounts for 50–80% of total cost of goods sold. For those firms, purchasing decisions cause enterprise wide side effects, and, therefore, should be treated as an integration matter. Supplier selection is a problem that deals with both qualitative and quantitative issues that must be measured using information that is normally spread within the enterprise. To see how this problem was addressed in a small construction company in Brazil, an integrated procurement process, which is a simplification of a more complex methodology, is presented. The case study shows the importance of simpler, yet efficient, solutions to address the decision making problems of smaller enterprises in development countries—a research and commercial niche not well developed yet.     

Evaluation of supplier capability and performance: A method for supply base reduction

Development of partnership with suppliers is widely recognised today as a potent tool for supply chain improvement. To develop an effective partnership, it is necessary to have a small supply base and an effort to reduce the supply base to a manageable level. Despite its overwhelming importance, models of supply base reduction are rare. Supplier sorting methods, used for pre-selection of suppliers and sometimes seen as methods for supply base reduction, have limitations ranging from (1) requirement of an exhaustive database of historical information (case-based reasoning), (2) inability to predefine the number of elements in a cluster (cluster analysis) and (3) inability to identify suppliers who are both highly capable as well as high performers (data envelopment analysis). In the present work, we develop a systematic framework for carrying out the supply base reduction process. The study assumes two important dimensions of suppliers—performance and capability. Performance of a supplier represents short-term effects on the achievement of supply chain objectives while supplier capability indicates long-term effects. Many of the performance and capability factors are imprecise in nature. In order to account for the imprecision involved in numerous subjective characteristics of suppliers, we use fuzzy set approach to measure the imprecision of these factors and rank a potential list of suppliers against their performance and capability. We then display their ranks in a ‘capability–performance matrix’ that helps a decision maker arrange the suppliers in decreasing order of preference. The desired numbers of suppliers are finally selected on the basis of this ordered list. The suggested framework will be of immense help to the practising managers in reducing the supply base—a prerequisite for building a strong supplier partnership and developing an effective supply chain.     

A multi-objective model for lot-sizing with supplier selection for an assembly system

Lot-sizing with supplier selection (LS-SS) is a fast-growing offspring of two major problem parents in logistics and supply chain management (‘lot-sizing’ and ‘supplier selection’). The model proposed in this paper is an attempt to extend it to an assembly system, by formulating a multi-objective model for an integrative problem of LS-SS for assembly items. The total costs of the system, consisting of purchasing, ordering, transportation, assembly, and holding, is considered the first objective function, while the total reliability of the finished products is considered the second objective function. The decision-maker aims to minimise the total costs while maximising the total reliability. Several constraints of the system (e.g. storage capacity, supplier production capacity) are taken into account. Given the complexity of the model, a heuristic evolutionary algorithm is proposed to solve the model. The results indicate which assembly items to order in which quantities, from which suppliers and in which time periods.     

Uncovering the supplier selection knowledge structure: A systematic citation network analysis from 1991 to 2017

Because of the critical role supplier selection plays in organizational success, both practitioners and academics have expressed a strong interest in the subject area generating an extensive body of research. The volume and breadth of publications in this area makes it difficult to understand the knowledge structure of the field and the academic work that has influenced the evolution of the domain.This mixed-method study systematically reviews 246 papers that investigated supplier selection issues and were published between 1991 and 2017. We initially examined the statistics of papers by unveiling influential journals, affiliations and articles. Second, we utilized co-citation network analysis, an objective procedure to extract clusters of what has been researched in supplier selection literature. The study analytically retrieves six major knowledge clusters: 1) conceptual foundation of the field; 2) modeling of the procurement environment; 3) handling group-decision making and unprecise input data; 4) computational research; 5) green/sustainable research and 6) risk-based supplier selection. Finally, we conducted main path analysis to get an overview of the evolution of knowledge in the supplier selection field by uncovering its major paths and key articles.