基于Nested Logit模型的IT外包供应商选择

提出一种基于Nested Logit模型的IT外包供应商选择的新方法.先通过联合分析法确定候选供应商的综合效用,在此基础上建立企业IT外包供应商选择的Nested Logit模型,从而得到企业按照自身需要来选择候选供应商的概率,最后应用贝叶斯的相关理论对该模型的假设前提进行了检验.     

基于“TOPSIS／DEA／AHP”模型的战略性供应商选择

研究了供应链环境下战略性供应商选择的问题.通过分析和总结供应商评价选择的准则、指标和方法,以供应链核心企业选择战略性供应商为目标,提出了战略性供应商评价的指标体系,利用整体DEA有效模型来反映供应商的绩效,利用AHP反映供应链核心企业选择供应商的主观愿望,从而构建了TOPSIS与整体DEA有效相结合的"TOPSIS/DEA/AHP"战略性供应商评价选择模型,并通过实证分析,证实了该模型及方法的可行性.     

一种多阶段供应商选择的混合整数规划模型

在建立供应链合作伙伴关系中,供应商的选择是供应链管理的一项重要内容.在现有文献的基础上对供应商的选择模型进行了改进,建立了集成单阶段与多阶段供应商选择的混合整数规划模型:既可以选择单阶段供应商,也可选择多阶段供应商即供应商的供应商的供应商等等.在模型中考虑了每个潜在供应商的能力约束,以供应商在产品价格、质量、配送水平等三个方面引起总的客户不满意度最小化作为选优的依据.     

基于BP神经网络和DEA的物流供应商选择

把交叉模型的评价结果设定为样本的期望值,将BP神经网络和交叉评价模型有机结合起来,构建了物流供应商选择模型。以2006年22家上市物流供应商的数据为样本进行了研究。该方法从统计数据出发,避免了主观因素对评价结果的影响,使物流供应商选择结果具有相对客观性。实例表明,该选择模型能够确定出备选物流供应商的评价等级和大小,为物流供应商的选择提供了一种新方法。     

基于贝叶斯方法的包装企业供应商评价与选择模型

目的建立基于贝叶斯方法的供应商选择模型。方法建立一个供应商选择动态过程,将供应商的历史信息与供应商提供的自身信息联系起来;利用贝叶斯方法对供应商达成采购企业目标的能力进行评判和修订,并进一步评估供应商风险。结果贝叶斯方法为包装企业评价和选择供应商提供了规避风险的有效手段,可以提高包装企业的竞争力。结论基于风险视角下的供应商选择与评价模型,是保证包装企业在控制供应商风险的前提下对供应商进行选择评价的重要工具。     

供应商逆向选择行为的成因与对策研究

从信息经济学的角度分析了供应商逆向选择行为出现的根本原因与必要条件,在此基础上探讨了如何利用供应商声誉和供应商利用信号显示原理来传递自身信息,以及采购企业通过实施选择与认证机制,或是通过显示原理设计报酬合同并根据供应商的选择结果来判断供应商的真实信息或类型,从而有效地降低了交易双方之间的信息不对称程度,并解决了供应商逆向选择问题.     

考虑不完全语义信息的风险型供应商选择方法

考虑供应商选择中决策者的风险态度,提出了一种考虑不完全语义决策信息的风险型供应商选择方法。结合二元语义模型和D数获取并处理决策者给出的不确定性和不完全的供应商评价信息,基于D数信息融合模型获取集结后的群决策信息。基于累积前景理论对候选供应商进行评价,考虑市场竞争获取前景价值函数,基于综合前景值最大化优化模型获得的指标权重对供应商进行排序。最后以挖掘机救援与现场维修服务供应商的评价与选择为例,验证了所提方法的有效性。     

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。     

考虑运输的多供应商采购模型及算法

考虑单产品多供应商和多运输业务采购决策问题。引入抵扣价值概念来处理采购量高于实际需求量的情况,分整运和零运两种情况研究了运输业务的选择对总成本、延期交货率、到货缺陷率等采购要素的影响,基于此提出了考虑运输的多供应商采购模型,并特别设计了编码和算子以便应用NSGA-II遗传算法,最后利用算例分析了模型和算法的有效性。     

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。     

Fuzzy hybrid decision model for supplier evaluation and selection

This paper proposes a structured, integrated decision model for evaluating suppliers by combining the fuzzy analytical hierarchy process (FAHP) and grey relational analysis (GRA). The qualitative and partially-known information is incorporated in this decision model using the fuzzy set theory. In this proposed methodology, the weights of the evaluation criteria are calculated by using FAHP, then the ranking of the suppliers is determined by using GRA. Finally to show the robustness of the model, a sensitivity analysis is also performed. In this study, the supplier selection problem of an electroplating industry in the southern part of India was investigated, demonstrating the effectiveness of this developed integrated model. This model can help in solving the complex decision in supplier selection practice. The results generated from the model are properly validated and finally a systematic solution with decision support is provided for decision makers. This model can be integrated with other decision support systems of similar kinds of industries.     

Integrated model for supplier selection and negotiation in a make-to-order environment

The paper deals with the development of an integrated supplier selection and negotiation process for multiple parts/materials procurement. The main objective is to integrate decisions in the internal supply chain of a make-to-order manufacturer. Two main decisions during the negotiation process are considered: (1) the manufacturing planning decision responsible for determining the production schedule and fabrication lot size and (2) the supplier selection decision concerning which suppliers are selected for company business and the order volume allocated to each selected supplier. The model is designed to support the negotiation process by generating a set of effective alternatives in each negotiation period. Its structure is multi-objective and non-linear. The combination of the interactive weighted Tchebycheff method and Benders decomposition method is applied to generate a set of effective alternatives to support the decision-maker in each negotiation period.     

An integration of a hybrid modified TOPSIS with a PGP model for the supplier selection with interdependent criteria

This paper deals with the supplier selection process when the criteria of selection are not independent. The primary aim is to illustrate that ignoring the interdependencies among these criteria leads to an unrealistic decision. Since supplier selection is a multiple-criteria decision-making (MCDM) process, the general structures of the relative methods are outlined in this paper. The proposed methodology then presents a comprehensive approach to find the best ranking among the alternative suppliers of a typical product. A hybrid modified TOPSIS is integrated with a preemptive goal programming model in this study and then compared to an analytical hierarchy process (AHP) to show the effect of considering interdependencies in the supplier selection process. The results indicate that the proposed methodology provides a higher total value of purchasing (TVP) than AHP while the total cost of purchasing (TCP) of both methods are equal. Empirical proof is offered based on a case study.     

A distinct decision model for the evaluation and selection of a supplier for a chemical processing industry

The supplier selection process has gained importance recently due to the considerable amount of revenue spent on purchasing. The intention of this work is to develop an appropriate hybrid model by integrating the analytical hierarchy process (AHP) and grey relational analysis (GRA) for supplier evaluation and selection, which comprises three stages. In Stage I, the most influential criteria are selected by mutual-information-based feature selection. Stage II focuses on the determination of the weights of the attributes using AHP, while Stage III is used for the determination of the best supplier using GRA. The proposed model is illustrated using the case study of an electroplating industry to highlight the effectiveness and flexibility of the model. The model effectively combines specialised knowledge, experience and quantitative data to select the best suppliers. This paper presents the model development, solution and application processes of the proposed hybrid model for supplier selection. The decision support software was implemented in Excel to automate supplier selection. The proposed hybrid model is applied to enhance the decision-making process in supplier selection and also helps decision makers to effectively select suppliers.     

Supply chain network design with unreliable suppliers: a Lagrangian relaxation-based approach

This paper deals with the integrated facility location and supplier selection decisions for the design of supply chain network with reliable and unreliable suppliers. Two problems are addressed: (1) facility location/supplier selection; and (2) facility location/supplier reliability. We first consider the facility location and supplier selections problem where all the suppliers are reliable. The decisions concern the selection of suppliers, the location of distribution centres (DCs), the allocation of suppliers to DCs and the allocation of retailers to DCs. The objective is to minimise fixed DCs location costs, inventory and safety stock costs at the DCs and ordering costs and transportation costs across the network. The introduction of inventory costs and safety stock costs leads to a non-linear NP-hard optimisation problem. To solve this problem, a Lagrangian relaxation-based approach is developed. For the second problem, a two-period decision model is proposed in which selected suppliers are reliable in the first period and can fail in the second period. The corresponding facility location/supplier reliability problem is formulated as a non-linear stochastic programming problem. A Monte Carlo optimisation approach combining the sample average approximation scheme and the Lagrangian relaxation-based approach is proposed. Computational results are presented to evaluate the efficiency of the proposed approaches.     

Design of an integrated supplier selection and multi-echelon distribution inventory model in a built-to-order supply chain environment

The paper deals with the development of an integrated supplier selection and multi-echelon distribution inventory model (MEDIM) for the original equipment manufacturing company in a built-to-order supply chain environment using fuzzy analytical hierarchy process (FAHP) and a genetic algorithm. The main objective is to design the integrated qualitative decision-making of the supplier selection model using FAHP with that of the quantitative mathematical model for the distribution inventory supply chain using a genetic algorithm to the built-to-order environment. The proposed model is validated by considering the case study in a tyre industry in Southern India. The software used for programming is C++ language.     

Global supplier selection: a fuzzy-AHP approach

Global supplier selection has a critical effect on the competitiveness of the entire supply chain network. Research results indicate that the supplier selection process appears to be the most significant variable in deciding the success of the supply chain. It helps in achieving high quality products at lower cost with higher customer satisfaction. Apart from the common criteria such as cost and quality, this paper also discusses some of the important decision variables which can play a critical role in case of the international sourcing. The importance of the political-economic situation, geographical location, infrastructure, financial background, performance history, risk factors, etc., have also been pointed out in particularly in the case of global supplier selection. Supplier selection problem related to the global sourcing is more complex than the general domestic sourcing and as a result it needs more critical analysis, which could not be found properly in past available literatures. This paper discusses the fuzzy based Analytic Hierarchy Process (fuzzy-AHP) to efficiently tackle both quantitative and qualitative decision factors involved in selection of global supplier in current business scenario. The fuzzy-AHP is an efficient tool to tackle the fuzziness of the data involved in deciding the preferences of the different decision variables involved in the process of global supplier selection. The triangular fuzzy numbers are used to transform the linguistic comparison of the different decision criteria, sub-criteria and performance of the alternative suppliers. The pairwise comparison matrices help in deciding the synthetic extent value of each comparison and finally, the priority weights of one alternative over another are decided in this paper. An example from a manufacturing industry searching for the global supplier for a critical component is used to demonstrate the effective implementation procedure of proposed fuzzy-AHP technique. The proposed model can provide the guidelines and directions for the decision makers to effectively select their global suppliers in the current competitive business scenario.     

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.     

A genetic algorithm based grey goal programming (G3) approach for parts supplier evaluation and selection

The problem of part supplier selection is a major concern for all manufacturers when seeking to enhance the products’ quality and productivity. The objective of this paper is to propose an integrated genetic algorithm based grey goal programming (G³) approach to solve the part supplier selection problem. The main factor in part supplier selection is the assembly relation of the parts so as to find the suitable suppliers combination for the parts of a product. We first identify the main factors affected on supplier selection. We then present a grey-based goal programming model to work as the fitness function to evaluate the suppliers with respect to the total deviation the factors have from the ideal values. Since the objective is to find the best solution, a genetic algorithm is used to solve this problem for faster and better evaluation. The novelty of this integrated approach is to apply both qualitative and quantitative factors at once in one model and to use the grey theory to cover the lack of information of qualitative factors in order to find a solution in a near real situation.     

确定供应商评价指标权重的一种方法

首先分析了供应链管理中供应商选择和评价的重要意义，然后对选择供应商的评价指标及权重的确定问题进行了分析；根据已有的评价方法中确定指标权重方法的某些不足，提出一个灰关联分析模型，试图从灰色系统理论角度来探讨这个问题，最后，选择了质量、成本、交货期3个常用指标，建立起了供应商选择和评价的指标权重灰关联分析模型，给出了一个数据计算过程示例，并对计算结果进行了分析和讨论。