绿色供应链下基于组合赋权的灰色关联TOPSIS法对供应商评价选择的研究

为了顺应绿色供应链发展的趋势,H企业与供应商建立绿色战略合作伙伴,实现双方的共赢。文章综合考虑了质量、服务、环境、成本、技术五大因素,建立了科学合理的供应商评价指标体系;采用FAHP法和熵值法对各指标进行主观和客观组合赋权,利用灰色关联TOPSIS法进行供应商评价排序,选出最佳的供应商作为绿色战略合作伙伴;最后通过算例计算以及结果对比分析,验证了FAHP/熵值法/灰色关联TOPSIS模型的稳定性和有效性。     

基于集对分析法的往复泵运行状态评估

往复泵是由多部件组成的复杂系统,在运行状态评估过程中,评估指标权重的确定和评估方法的选择是其核心内容。往复泵的运行状态评估指标较多,为了科学、准确地把握往复泵运行状态,将模糊集值统计法、熵值法和集对分析理论引入到往复泵的运行状态评估中,并对集对分析联系度的确定方法进行拓展。基于模糊集值统计确定主观权重初始权重,基于熵值法对主观初始权重动态调整得到各指标的综合权重,并基于改进的集对分析方法,建立往复泵运行状态评估模型,最后通过现场实例分析验证其可靠性。     

油气管道第三方破坏风险管理效能评估方法研究

在油气管道第三方破坏风险管理效能评估中,存在十分复杂的影响因素和关联性。针对第三方破坏风险管理的特点,依据事故过程关联因素建立效能评估指标体系,运用多属性决策效能评估加权的TOPSIS方法,对从5个不同管道公司获取的指标调查结果进行整体性效能综合评估。其中,利用改进的灰靶理论的贡献度算法确定加权TOPSIS方法中的各指标权重。应用案例分析表明,这种方法的评估结果具有一定的准确性和合理性。     

Construction Planning Decision of Subway Stations Based on AHP-TOPSIS Method

AHP和TOPSIS相结合可以实现评价方法的易操作性,提高结果的客观和准确程度.文章建立地铁车站方案优化排序的数学模型,对大连地铁1号线海事大学车站施工方案进行比选.通过实地调研和文献查阅完成专家调查表,采用AHP法计算各指标的权重,并用改进的TOPSIS法进行评价指标值的规范化和排序计算,最终确定选择方案.     

芦山小流域水土保持综合整治工程项目管理评估探析

针对水土保持项目重于建设而疏于管理,导致项目后期综合效用降低等问题,从管理机构与制度、投资及收益、技术推广、工程维护与管理4方面入手,采用基于熵权的改进TOPSIS法对芦山小流域水土保持综合整治工程项目管理各时期的综合效用实施评估。同时,针对项目各时期管理运行效用评估结果提出优化对策,以期为水土保持项目的管理运行策略制定提供决策依据。     

基于信息熵-VIKOR模型的4PL供应商优选决策研究

第四方物流（4PL） 凭借其在供应链资源整合方面的独特优势， 在供应链管理中发挥着日益重要的作用。本文基于4PL 供应商的特征分析， 挖掘出影响4PL 供应商选择的主导因素并构建了包括供应链资源整合能力、风险管理能力、数据信息处理能力、管理组织能力及市场竞争能力在内的评价指标体系。通过客观赋值方法——信息熵法确定评价指标体系权重， 构建了通过引入灰色关联系数改进VIKOR方法下的4PL供应商优选决策模型。最后， 对4PL 供应商进行优选决策的实证研究。研究结果表明， 本文构建的评价指标体系及基于信息熵－VIKOR模型的优选决策模型在新经济条件下4PL 供应商优选策中具有较强的科学性及适用性。     

制造业企业可靠性体系成熟度评价

为提升制造业企业可靠性发展水平，建立并完善企业可靠性体系，加强质量技术攻关和可靠性提升工程建设，从技术、管理、保障3个维度构建制造业企业可靠性体系成熟度评价模型，为制造业企业提供了一套标准化的可靠性体系成熟度的度量方法，可供企业可靠性能力的评核和可靠性的持续改进优化。     

油气管道应急救援能力评估方法研究

为有效地评估和提高油气管道企业的应急救援能力,提出一种基于组合赋权的评估方法。结合工程实际,建立了油气管道企业应急救援能力评估的指标体系。为提高评估的准确性,采用组合赋权模型将层次分析法和熵权法所得权重进行融合。根据评估分值确定应急救援能力的水平。实例分析表明,应急准备能力和应急响应能力对应急救援能力的影响最大,应作为日常管理的重点;实例中输气站A的应急救援能力等级为一般,需要加强救援队伍建设和应急预案响应等方面的工作。     

基于RF-LSMA-SVM模型的中小微企业信用风险评价研究

针对中小微企业的融资难问题,应对传统的信用风险评级方法进行改进。本文以我国2021年新三板中小微企业为样本,加入管理层角度的新指标,使信息更加完整。另外改进了经典的黏菌算法(SMA),结合基础支持向量机模型(SVM)进行参数优化,建立了RF-LSMA-SVM模型,考察信用风险判定问题。结果表明,管理层各角度、企业偿债能力和企业盈利能力等方面的指标对于信用风险均具有一定的解释能力,而企业的客户结构和企业性质是冗余信息。在大数据背景下,银行和中小微企业可以利用所构建的RF-LSMA-SVM模型进行信用风险评级来增强分类能力。本文研究结果补充了信用风险评级指标,也完善了评级模型,对提高评级准确性具有启示意义。     

基于改进灰色预测模型的供应链韧性评价与预警研究北大核心

在不确定环境下,更高的供应链韧性可以有效降低中断风险,帮助企业实现高质量经营。本文从供应链的视角构建一种面向制造企业的韧性评价指标体系,并使用改进TOPSIS方法量化韧性的水平。考虑现实环境中韧性指标易受到非常规因素的影响,引入WAWBO弱化缓冲算子及新陈代谢思想来改进灰色预测方法,从而实现韧性指标的动态预测。同时,结合韧性量化方法,构建了一种供应链韧性预警模型。以国内一家电子制造企业2020~2022年的数据进行实证研究,结果表明TOPSIS韧性量化方法的有效性,所提出的改进灰色预测方法也具有更高的预测精度,平均预测误差为2.91%。研究为相关企业提高供应链韧性预警能力、实现供应链的可持续发展提供新思路。     

基于供应链的煤炭企业供应商管理研究

煤炭企业的生产特点和物资需求特性,决定了煤炭企业应该进一步改革物资采购模式,完善供应商管理工作。为有效跟踪供应商绩效表现,降低供应链风险,基于供应链管理理论提出目前中国煤炭企业应实施供应商全生命周期管理,并将供应商分类、供应商评价体系和关系管理纳入企业信息化系统建设中,有助于企业实现全方位的供应商关系管理。     

大型煤炭企业供应商管控模式构建与实践

以冀中能源股份有限公司为例,论述了煤炭企业构建供应商管控模式的必要性和可行性,通过对物资采购管理模式的不断摸索、总结归纳和持续创新,建立了动态管理的物资采购供应商管控新模式,形成了对供应商规范、科学的评价选择体系,从而实现物资管理合理化、效益最大化,提高企业的竞争力。     

Suppliers capability and price analysis chart

To remain competitive in customer-oriented economics, the major parties in the supply chain should be integrated and managed effectively to respond to customer needs. Thus, the efficiency of the entire supply chain is a main concern, and is determined by the members of that supply chain. Partner selection thus becomes one of the key steps in supply chain construction. Given buyer–supplier information asymmetry, obtaining complete information from suppliers is difficult, since some supplier attributes cannot be definitely and quantitatively measured. This study establishes a suppliers capability and price analysis chart (SCPAC) focused on the case where the specification limits are symmetric about the target for evaluating supplier performance which applies the process incapability index C_pp introduced by Greenwich and Jahr-Schaffrath (International Journal of Quality & Reliability Management 12 (1995) 58) to measure supplier quality performance and the price index I_p is proposed here to display the difference between budget and component price. Practitioners can instantly and visually obtain information based on the locations of suppliers and price indices on SCPAC. SCPAC also provides clear directions for quality improvement, such as process accuracy and precision. SCPAC thus is an effective and efficient method for evaluating suppliers, which can simplify supplier evaluation, facilitate their effective visual selection, and provide insights into the process situation of suppliers who can become technological innovation partners.     

Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle

Owing to rapidly growing global competition, enterprises are increasingly focusing on their core competencies. The focal company faces the challenge of creating alliances with more suppliers to create outsourcing synergy and provide heterogeneous products for customers. This study proposes a fuzzy multiple attribute decision making (FMADM) method based on the fuzzy linguistic quantifier. An attempt is made to ensure that the evaluation results satisfy the current product competition strategies, and also improve the effectiveness and efficiency of the entire supply chain. The fuzzy concept is applied to both the ordinal and cardinal information. Furthermore, the fuzzy linguistic quantifier guided order-weighted aggregation (FLQG-OWA) operator can be used to satisfy the enterprise product development strategy based on different phases of product life cycle.     

A Model of Supplier Integration into New Product Development*

In many industries, firms are looking for ways to cut concept‐to‐customer development time, to improve quality, and to reduce the cost of new products. One approach shown to be successful in Japanese organizations involves the integration of material suppliers early in the new product development cycle. This involvement may range from simple consultation with suppliers on design ideas to making suppliers fully responsible for the design of components or systems they will supply. While prior research shows the benefit of using this approach, execution remains a problem. The processes for identifying and integrating suppliers into the new product development (NPD) process in North American organizations are not understood well. This problem is compounded by the fact that design team members often are reluctant to listen to the technology and cost ideas made by suppliers in new product development efforts. We suggest a model of the key activities required for successful supplier integration into NPD projects, based on case studies with 17 Japanese and American manufacturing organizations. The model is validated using data from a survey of purchasing executives in global corporations with at least one successful and one unsuccessful supplier integration experience. The results suggest that (1) increased knowledge of a supplier is more likely to result in greater information sharing and involvement of the supplier in the product development process; (2) sharing of technology information results in higher levels of supplier involvement and improved outcomes; (3) supplier involvement on teams generally results in a higher achievement of NPD team goals; (4) in cases when technology uncertainty is present, suppliers and buyers are more likely to share information on NPD teams; and (5) the problems associated with technology uncertainty can be mitigated by greater use of technology sharing and direct supplier participation on new product development teams. A supplier's participation as a true member of a new product development team seems to result in the highest level of benefits, especially in cases when a technology is in its formative stages.     

A decision method for supplier selection in multi-service outsourcing

Although supplier selection in multi-service outsourcing is a very important decision problem, research concerning this issue is still relatively scarce. This paper proposes a decision method for selecting a pool of suppliers for the provision of different service process/product elements. It pioneers the use of collaborative utility between partner firms for supplier selection. A multi-objective model is built to select desired suppliers. This model is proved to be NP-hard, so we develop a multi-objective algorithm based on Tabu search for solving it. We then use an example to show the applicability of the proposed model and algorithm. Extensive computational experiments are also conducted to further test the performance of the proposed algorithm.     

Supplier segmentation using fuzzy logic

Supplier segmentation means that the suppliers of a specific firm are categorized on the basis of their similarities. This supply-side business-to-business (B2B) segmentation is of special importance to companies with many suppliers. Supplier segmentation yields a manageable number of segments, each of which requires a separate strategy. Standard supplier segmentation methods have serious shortcomings, for instance because they fail to make a proper connection between supplier segmentation and other supplier-related activities such as supplier selection and development. Moreover, these standard methods typically use a limited number of segmentation criteria and different sets of criteria are suggested for each method. It is unclear for practitioners how to choose a particular method. The purpose of this paper is to form a practical tool for supplier segmentation taking into account all suggested segmentation criteria. The principal result of this paper is the design of a rule-based method to segment the suppliers of a firm based on two overarching dimensions: supplier capabilities and supplier willingness. The method is applied to a real-world situation to show how the results can be used in practice. A general sensitivity analysis procedure for fuzzy rule-based systems is proposed and then implemented, to identify the most important supplier capabilities and willingness criteria and to formulate better supplier development strategies. A major conclusion of the paper is that the fuzzy logic approach to supplier segmentation is simple to apply in practice, yet considers all available segmentation criteria and their inherent fuzziness in a way that is easily adaptable to a specific industrial context.     

A weighted max-min model for fuzzy multi-objective supplier selection in a supply chain

Supplier selection is one of the most important activities of purchasing departments. This importance is increased even more by new strategies in a supply chain. Supplier selection is a multi-criteria decision making problem in which criteria have different relative importance. In practice, for supplier selection problems, many input information are not known precisely. The fuzzy set theories can be employed due to the presence of vagueness and imprecision of information. A weighted max-min fuzzy model is developed to handle effectively the vagueness of input data and different weights of criteria in this problem. Due to this model, the achievement level of objective functions matches the relative importance of the objective functions. In this paper, an analytic hierarchy process (AHP) is used to determine the weights of criteria. The proposed model can help the decision maker (DM) to find out the appropriate order to each supplier, and allows the purchasing manager(s) to manage supply chain performance on cost, quality and service. The model is explained by an illustrative example.     

A two-stage model for the design of supply chain networks

This research aims to develop an analytical model of the supplier selection process in designing a supply chain network. The constraints on the capacity of each potential supplier are considered in the process. The assumed objective of the supply chain is to minimize the level of customer dissatisfaction, which is evaluated by two performance criteria: (i) price and (ii) delivery lead time. The overall model operates at two levels of decision-making: the operational level and the chain level. The operational level concerns decisions related to optimizing the manufacturing and logistical activities of each potential supplier in order to meet the customer's requirements. At the chain level, all the bids from potential suppliers are evaluated and the final configuration of the supply chain is determined. The structure of the chain depends on the product specifications and on the customer's order size. An optimal solution in terms of the models for the two levels can be obtained by using a mixed-integer programming technique.