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 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.     

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。     

Implementing of a three-phase integrated decision support model for parts machining outsourcing

Parts machining outsourcing (PMO) can be regarded as a strategic weapon to increase product quality and productivity as well as cost cutting in many manufacturing enterprises. However, making an outsourcing decision based on accumulated experience is neither effective nor scientific due to subjective judgement and lack of systematic analysis. Therefore, to systematically help the decision-maker survey and select suppliers to outsource and also to timely achieve the most beneficial portfolio among suppliers in a non-cooperative game structure, this paper proposes an integrated decision support model for PMO using ontology, constraint-based reasoning, fuzzy VIKOR and game theory in three phases, namely supplier prequalification, ultimate selection and order coordination. In the decision-making process, decision factors such as quality, cost and production capability are categorised and put into different phases, respectively, by their characteristics for being measured at a more reasonable method. Finally, a case from a leading printing machinery enterprise is analysed to validate the proposed model. This research is expected to improve the quality and effectiveness of decision-making in PMO.     

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.     

An integrated weighted fuzzy multi-objective model for supplier selection and order scheduling in a supply chain

This paper presents a new weighted fuzzy multi-objective model to integrated supplier selection, order quantity allocation and customer order scheduling problem to prepare a responsive and order-oriented supply chain in a make-to-order manufacturing system. Total cost and quality of purchased parts as well as the reliability of on-time delivery of customer orders are regarded as the objectives of the model. On the other hand, flexible suppliers can contribute to the responsiveness and flexibility of entire supply chain in the face of uncertain customer orders. Therefore, a mathematical measure is developed for evaluating the volume flexibility of suppliers and is considered as the other objective of the model. Furthermore, by considering the effect of interdependencies between the selection criteria and to handle inconsistent and uncertain judgments, a fuzzy analytic network process method is used to identify top suppliers and consider as the last objective. In order to optimise these objectives, the decision-maker needs to decide from which supplier to purchase parts needed to assemble the customer orders, how to allocate the demand for parts between the selected suppliers, and how to schedule the customer orders for assembled products over the planning time horizon. Numerical examples are presented and computational analysis is reported.     

Using integrated fuzzy DEMATEL and fuzzy C: means algorithm for supplier evaluation and selection

Decision-making techniques are used to help evaluate the current suppliers’ aim at classifying performance of individual suppliers against desired levels of performance, so as to design suitable plans to increase the performance and capabilities of suppliers. In this study, an integrated model is introduced and proposed for increasing the supplier selection and evaluation quality. The methodology is composed of two steps. The first stage is fuzzy decision-making trial and evaluation laboratory method in which the interactions between the evaluation criteria and the criteria weight have been computed. At the second stage, performances of suppliers are assessed using both the criteria weights obtained at the first stage and fuzzy c-means clustering algorithm by classifying the vendors according to their performances. Obtained results show that the proposed model is very well suited as a decision-making tool for supplier selection decisions.     

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.     

基于不确定语言信息的物流供应商选择

为解决传统供应商的选择与评价过程中专家评判的模糊性和不确定性问题,提出了一种基于不确定语言信息的物流服务供应商选择方法。该方法以不确定语言变量来表征专家的评判从而避免了决策信息的丢失。继而建立了物流服务质量评价属性的权重优化模型,并构造拉格朗日函数来求解该模型,得到评价属性的最优权重。接着利用不确定语言加权几何平均（ULWG）算子集结专家评判信息,则得到供应商的优先排序。给出了基于不确定语言信息的供应商选择的算法步骤和应用实例。     

A novel approach for supplier selection based on the Kano model and fuzzy MCDM

This paper proposes a three-phase approach for supplier selection based on the Kano model and fuzzy Multi Criteria Decision-Making. Since the supplier selection problem involves different criteria, quality attributes have been assumed to denote the importance weight of the criteria for supplier selection. Furthermore, to consider the inherent vagueness of human thought, a fuzzy logic has been utilised. Initially, the importance weight of the criteria has been calculated using a fuzzy Kano questionnaire and fuzzy analytic hierarchy process. In the second phase, the Fuzzy TOPSIS technique has been used to screen out in capable suppliers. Finally, in the third phase, the filtered suppliers which are qualified, once again will be evaluated by the same approach for the final ranking. The proposed approach has also been examined in a case study.     

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 integrated fuzzy multi-criteria group decision-making approach for green supplier evaluation

Purchasing is one of the most vital functions within a company and supplier performance evaluation is one of the most important business processes of the purchasing function. Traditionally, companies have considered factors such as price, quality, flexibility, etc. while evaluating suppliers. However, environmental pressures urge them to consider green issues. This study proposes a decision model for supplier performance evaluation by considering various environmental performance criteria. An integrated, fuzzy group decision-making approach is adopted to evaluate green supplier alternatives. More precisely, a fuzzy analytic hierarchy process (AHP) is applied to determine the relative weights of the evaluation criteria and an axiomatic design (AD)-based fuzzy group decision-making approach is applied to rank the green suppliers. Finally, a case study is given to demonstrate the potential of the methodology.     

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.     

A supplier pre-selection model for multiple products with synergy effect

In practice, it is common for companies to purchase multiple products simultaneously. For the multiple required products, a large number of interested suppliers are involved. It is necessary for the purchasing company to shortlist a small number of qualified and competitive potential suppliers prior to finalising the suppliers for order fulfilment. In addition, synergy effect which is an effect arising between two or more products that produce an effect greater than the sum of their individual effects, could exist in the multi-product supplier selection environment. Since synergy effect between products can affect the choice of suppliers, it is also necessary to incorporate the synergy effect between products in the supplier selection for multiple products. However, few research efforts have been focused on the supplier pre-selection problem, let alone explicitly for multiple products with synergy effect. This paper presents a supplier pre-selection model for multiple products with synergy effect. The model is able to evaluate interested suppliers on the multiple pre-selection criteria, by the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-based supplier pre-selection algorithm, and shortlist a small number of potential suppliers. Illustrative examples are conducted to demonstrate the function and application of the supplier pre-selection model for multiple products with synergy effect.     

Supplier selection using fuzzy association rules mining approach

Owing to ill-structured, dynamic environments and the presence of multiple decision-makers with conflicting viewpoints, comprehension, analysis and support of the supplier evaluation process becomes more and more difficult. Moreover, with the complexities of issues such as the role of leadership, the influence of group formation, and analysis of disagreements, it cannot be predictable that there will ever exist a solution to cope with all imprecise, multi-criteria/multi-actor situations. A fuzzy association rules-based approach may be suited for the judgement of human subjects. In this paper, we develop an approach based on Fuzzy Association Rule Mining to support the decision makers by enhancing the flexibility in making decisions for evaluating suppliers with both tangibles and intangibles attributes. Also, by checking the fuzzy classification rules, the goal of knowledge acquisition can be achieved in a framework in which assessments could be established without constraints, and consequently checked and compared in several details. The efficacy and intricacy of the proposed model for finding fuzzy association rules from the database for supplier assessment is demonstrated with the help of numerical examples.     

Supplier Selection Fuzzy Model in Supply Chain Management: Vietnamese Cafe Industry Case

Supplier selection is a vital part of the supply chain and is also a current issue that concerns businesses today as supplier quality directly affects the operations of the organization. Choosing the right supplier can help businesses increase productivity, competitiveness in the market, and profits without having to lower the quality of the products. However, choosing a supplier is not a simple matter, it requires businesses to consider many aspects about their suppliers. Therefore, the goal of this study is to propose an integrated model consisting of two models: Fuzzy Analytics Network Process (Fuzzy-ANP) model and Weighted Aggregated Sum Product Assessment (WASPAS) to solve the problem above. The Fuzzy-ANP model was developed to evaluate the weightings of the supplier selection criteria, and the WASPAS Model was used to rank the suppliers. An example of supplier selection in the coffee industry in Vietnam was studied to validate the model, namely 5 main criteria, with 16 sub-criteria, and 7 suppliers. The model test results show that the Fuzzy ANP and WASPAS integration model was suitable. In future, these developing models can apply to other industries or integrate with other models.     

Two-phase selection framework that considers production costs of suppliers and quality requirements of buyers

Buyers are faced with selecting the optimal supplier, while suppliers are left to consider production costs. In this study, we developed a two-phase selection framework that allows buyers to evaluate the performance of suppliers while taking production costs into account for value maximisation. This scheme is a win-win solution capable of promoting long-term relationships between buyers and suppliers. Under the assumption of normality, the first phase involves constructing a new Six Sigma quality capability analysis chart (SSQCAC) which takes production costs into account. The objective is to evaluate all potential suppliers using the 100?×?(1–α)% upper confidence limit (UCL) of an integrated Six Sigma quality index (SSQI) Q_PIh when dealing with products with smaller-the-better (STB), larger-the-better (LTB), or nominal-the-best (NTB) quality characteristics. According to interval estimation theory, this method can have a significant impact on the consumption of resources; i.e. the production costs of the supplier can be decreased by reducing the production quality to below that required by the buyer. The proposed method also filters out unsuitable suppliers in order to simplify the decision problem and reduce computational demands and operational risks/costs without compromising the quality of the final product. In the second phase, a detailed analysis is conducted using Euclidean distance measure to select the optimal supplier from among the remaining candidates. We conducted a real-world case study to evaluate the efficacy of the proposed method. We also conducted comparisons with existing methods to demonstrate the advantages of the proposed method and its managerial implications. Suggestions for future study are also provided.     

基于FMEA的军队第三方物流供应商选择

目的 针对军队第三方物流供应商的选择问题,从风险视角对供应商完成军事保障任务过程中可能存在的风险进行识别和评估,以降低军事物流外包风险,为军队第三方物流供应商决策提供方法和思路。方法 提出可将FMEA技术运用于军队第三方供应商选择中的操作性框架,按照框架流程确定评价标准、识别潜在失效模式、决策分析,可更加全面、科学地对军队第三方供应商做出选择。结果 在不考虑风险的情况下,5家候选供应商中E的原始评分最高,D排名居中,但经过FMEA分析后,由于E在单项评价指标上的风险比例太大,而D的各项指标风险比原始排名靠前的供应商小很多,因此D成为军队最终选择的供应商。结论 利用FMEA分析军队第三方物流供应商选择问题,可以起到事先识别可能出现的失效模式,分析产生原因和可能导致的后果以及现有措施的可控程度,从而评估每位候选供应商在确定的评价标准中的风险大小,最后综合原始评分得出了供应商选择的结果。该方法操作简单、计算方便,能比较全面衡量军队第三方物流供应商的综合水平,有助于提高军队物资保障效率,降低物资保障风险。     

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 utility-driven approach to supplier evaluation and selection: empirical validation of an integrated solution framework

Supplier evaluation and selection (SES) problems have long been studied, leading to the development of a wide range of individual and hybrid models for solving them. However, the lack of widespread diffusion of existing SES models in the industry points to a need for simpler models that can systematically evaluate both qualitative and quantitative attributes of potential suppliers while enhancing the flexibility decision-makers need to account for relevant situational factors. Furthermore, empirical validations of existing models in SES have been few and far between. With a view to addressing these issues, this paper proposes an integrated solution framework that can be used to evaluate both tangible and intangible attributes of potential suppliers. The proposed framework combines three individual methods, namely the fuzzy analytic hierarchy process, fuzzy complex proportional assessment and fuzzy linear programming. The framework is validated through application in a Turkish textile company. The results generated using the proposed framework is compared with the actual historical data collected from the company. Additionally, a feasibility assessment is conducted on the sample supplier selection criteria employed, as well as assessment of the results generated using the proposed model.