应用FCEM对供应链合作伙伴进行评价

供应链合作伙伴的评价选择是供应链管理研究的一个重要方面,本文采用模糊综合评价方法(FCEM)建立了供应链合作伙伴的评价与选择的综合评价模型,并进行了实证分析。     

供应链合作伙伴的选择和评价

供应商的选择和评价是供应链管理的重要内容,也是供应链管理成功的关键因素之一。本文针对供应商合作伙伴的选择和评价,提出了供应商评价的四层面指标模型和供应商分步选择过程。另外,应用改进的加权平均法评价指标模型中的“产品”指标,应用AHP方法量化定性指标。所提出的方法和手段在实际应用中得到了验证,取得了满意的效果。     

供应链合作伙伴选择的两阶段模型方法研究

合作伙伴的选择是供应链管理中一个非常重要且复杂的环节.针对合作伙伴选择的问题,分析了供应链合作伙伴选择过程应遵循的原则,给出了合作伙伴选择的二阶段模型及其实现方法.     

关于模糊综合评价方法下的供应链合作伙伴选择

在供应链管理环境下,供应商选择是供应链管理中的一个重要环节,供应商选择的科学与否,直接关系到企业的生存与发展,文章综合层次分析法（AHP）和模糊选择,提出了基于层次分析的供应链合作伙伴的模糊选择方法。这种方法通过AHP方法确定各目标权重,用模糊综合评价方法进行评判,既体现决策者的主观意向,又反映了客观的信息,为确定供应链合作伙伴提供了一种综合评价方法。最后给出了一个数值例子来例证该方法的实际应用。     

基于FANP方法的供应链配送中心评价选择

供应链配送中心的评价选择是供应链管理的重要课题.层次分析法(AHP)只能分析经过大量简化处理的树状结构或者其他理想结构.因此,采用解释结构模型(ISM)建立配送中心评价选择指标体系,用模糊网络分析法(FANP)进行计算分析,对以制造业为主导的供应链配送中心进行评价和选择,不仅考虑了指标的层次关系,也考虑到各层中因素之间的相互关系,解决了对具有网络关系的混合型结构评价指标体系的评价选择问题,克服了层次分析法(AHP)等传统算法的局限,在实际应用中具有很好的效果.     

基于动态扣分的合格供方评价方法

本文通过将缺陷扣分法、加分法、预警机制等管理要素引入供方评价过程,为企业提供一套全新的动态扣分供方评估方法。希望通过该方法的引入,降低企业合格供方管理的成本,提升管理的有效性。     

第三方逆向物流评价决策支持系统探讨

第三方逆向物流对现代供应链管理的影响越来越大,如何科学、合理地评价选择物流服务商,直接关系到物流需求方企业及其供应链管理的效率和效益.文章在分析了传统的供应商评价选择方法的基础上,提出一种基于案例推理(CRB)的第三方逆向物流评价决策支持系统的模型框架.     

应用供应链管理思想改造传统工业企业

供应链管理是现代工业企业最先进的管理思想和,应用供应链管理思想对传统工业企业进行改造是一种可行的选择。在实施改造过程中，出发点应是培育，巩固和提高企业的核心竞争力，主要内容包括供应链设计，先进管理方法的应用和员工培训等。     

电网企业供应商关系管理模式研究与应用

在国网公司物资集约化管理深入推进的背景下,供应商是整个供应链的源头。本文在分析供应商选择和评价工作重要性的基础上,阐述了公司开展供应商选择和评价工作的程序和方法,提出了具体的评价指标体系,并对其在实际工作中的应用提出了一些探索。     

物资采购过程中对供方的管理

物资采购过程中,如何加强对供方的管理,对于采购活动的有效完成至关重要。本文对供方管理过程中选评原则、选评依据、选评步骤以及对供方如何控制进行了阐述。     

A multi-agent architecture for multi-product supplier selection in consideration of the synergy between products

Supplier selection is an important task in purchasing. The performance of a supply chain depends on the selection of the right suppliers to provide the right materials or services at the right price and right time. Most of the research on supplier evaluation and selection assumes that products are procured independently. However, in reality, it is common for a purchasing company to procure a bundle of products together. In this regard, synergy could exist between products and hence affect the final choice of suppliers. It is therefore necessary for the purchasing company to incorporate the synergy between products in supplier selection. This paper presents a multi-agent system (MAS) architecture for multi-product supplier selection in consideration of the synergy between products. A three-phase supplier selection model is proposed to support multi-product procurement in consideration of the synergy between products. The three phases are, namely, product synergy determination phase, supplier pre-selection phase and negotiation-based final selection phase. The MAS is equipped with various types of autonomous function agents and different agent interaction protocols to effect the functioning of this three-phase multi-product supplier selection model.     

Supplier Selection Based on Process Capability and Price Analysis

Supplier selection is an important part of supply chain management. Among the numerous methods that have been proposed, process capability index is considered to be the most effective technique for identifying quality parts. However, supplier selection should be carried out on the basis of quality and cost together. There is no easy tool available to evaluate the price and quality in an integrated manner. In this article, a new approach to supplier selection using capability index and price comparison (CPC) chart is presented. The CPC chart integrates the process capability and price information of multiple suppliers and presents them in a single chart. It provides a simple but effective method to consider quality and price simultaneously in the supplier selection process.     

产品生命周期过程(横向集成)供应商选择模型研究

通过分析集成化供应链管理环境下供应商选择过程,给出了选择指标体系及选择步骤。在此基础上,建立了“横向”集成型企业供应商选择的模糊综合评价选择模型。应用此模型可对选择最满意的供应商做出相应的决策。     

A hybrid multi-agent negotiation protocol supporting supplier selection for multiple products with synergy effect

Supplier selection is an important problem in supply chain management. In practice, it is common for a purchasing company to procure a bundle of products simultaneously. In this regard, synergy effect could exist between products and hence affect the final choice of suppliers. It is therefore necessary to incorporate the synergy effect between products in supplier selection process. Agent-based negotiation models are applied to automate supplier selection process. Negotiation protocol is an essential component should be considered when building an effective agent negotiation model. The objective of this research is to propose a negotiation protocol special for multi-product supplier selection problem. The negotiation protocol is a hybrid multi-agent protocol of combinatorial procurement auction protocol and multi-bilateral bargaining protocol. The negotiation protocol is able to support the purchasing company and suppliers negotiate on the concrete commitments of multiple products simultaneously, and select suppliers for multiple products. In addition, both the purchasing company and suppliers can express their preferences on the synergy effect between products in negotiation process by adopting the negotiation protocol. Simulation is conducted to demonstrate the effectiveness and efficiency of the negotiation protocol.     

Bootstrap approach for supplier selection based on production yield

Current manufacturing industries have increased their level of out-sourcing and relied more heavily on their supply chain as a source of competitive advantage. Supplier selection decisions have become an important component of production management. Those decisions have a significant impact on a firm's marketing competition, and suppliers may account for a large portion of the production cost. Production quality is one of the key factors in supplier evaluation. The manual of supplier certification includes a discussion of process capability analysis, which recommends a procedure for evaluating the most prevalent process capability index C _pk. However, the recommended procedure is applicable only when evaluating an individual supplier's performance. In this paper, we apply the bootstrap method to the supplier selection problem. We construct lower confidence intervals for the capability difference and ratio between two given suppliers. Performance comparisons are made among various bootstrap methods in terms of error probability and selection power. For convenience of applications, the sample sizes required for various designated selection power are also tabulated.     

A model for performance monitoring of suppliers

The purchasing function is central to the strategic operations of effective supply chain management. This centrality is mainly due to the significant impact of material costs on profits, increased investments in inter-organizational advanced manufacturing and information technologies, and a growing emphasis on the just-in-time operations philosophy. The critical business processes of the purchasing function include supplier selection, negotiation of supply contracts, monitoring supplier performance, and acting as an interface between an organization and its suppliers. Within these core processes of purchasing, this paper narrows its scope to focus upon the supplier performance evaluation and monitoring process, which assists in maintaining effective customer-supplier linkages. While price has been traditionally considered as the single most important factor in evaluating suppliers, it has been agreed upon that value performance emphasis needs to include other important factors such as quality, delivery and flexibility. Given this evolving business competitiveness environment, the contribution of this research is threefold. First, it applies a new multi-criteria evaluation model for supplier performance evaluation by considering various performance criteria. Second, a proposed application extension of this model serves as a monitoring and control mechanism for the performance of suppliers, thus supporting continuous process improvement to achieve efficient customer-supplier relationships. Third, the paper presents this technique as a new methodological extension to data envelopment analysis research by improving the discriminatory power of an existing variable returns to scale model. The model and its application are demonstrated through a previously published illustrative case example.     

Models for supplier selection and risk mitigation: a holistic approach

According to a study conducted by PwC and the Business Continuity Institute in 2013, 75% of companies experience at least one major supply chain disruption a year and majority of the disruptions were caused by supply-related problems. With an increasing emphasis on upstream risk, risk management in supplier selection has become a critical issue faced by companies. Although previous studies proposed different methods and tools for effective and efficient supplier selection, only few approaches have attempted to incorporate risk mitigation strategies in supplier selection decisions. Our study aims to fill this gap by considering a wide range of quantitative and qualitative risk factors in supplier selection and evaluates the efficacy of alternative risk mitigation strategies in this context. Moreover, we suggest that both upstream and downstream strategies should be utilised simultaneously rather than relying on a single type of strategy. We further suggest that it is critical to align upstream and downstream risk mitigation strategies to reduce risk. We employ multi-objective optimization-based simulation in developing a decision model and consider data from an automotive parts manufacturer to demonstrate the application of our approach.     

Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic

As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.     

基于供应链管理的供应商选择问题初探

首先讨论了供应链环境下选择供应商的意义，然后建立了供应商选择的评价指标体系，重点讨论了应用TOPSIS 方法对供应商选择的模型及算法，最后用一个简单的案例进行了说明。     

A hybrid risks-informed approach for the selection of supplier portfolio

In conventional supplier selection approaches, cost consideration is usually emphasised and it renders a vulnerable supply chain with various risks. This article aims to develop a quantitative approach for modelling both supply chain operational risks and disruption risks to support decision-making with regard to order allocation and risk mitigation. We introduce two types of risk evaluation models: value-at-risk (VaR) and conditional value-at-risk (CVaR). Specifically, VaR is used to measure operational risks caused by improper selection and operations of a supplier portfolio to the stochastic demand, which may frequently occur but result in relatively small losses to supply chains; CVaR is used to evaluate disruption risks that are less frequent and tend to cause significant damage. After incorporating risk factors into a probability-based multi-criteria optimisation model, different methods and parameters are compared and tested to determine the factors that may influence the supplier selection process. Computational examples by simulation are presented to illustrate the approach and how decision-makers make trade-offs between costs and hybrid risks.