Selection Model in Buyer-Supplier Relationships

This paper proposes a new method of selecting appropriate buyer supplier relationships (BSR) for specific projects. Because it is almost impossible in reality to establish mathematical relationships between the BSR attributes and the factors of a project, the concept of relationship indices (RI) is introduced to quantify such BSR which are in turn established through design of experiments. Based on the experimental results, the contributions of project factors, known as factors relationship worths (RW...

Impact analysis of supplier relationship on supply chain resilience using biological cellular resilience theory

A supply chain resilience model is established based on the biological cellular resilience theory to analyze the impact of the supplier relationship on supply chain resilience. A scenario where the market demand is changed suddenly by some undesired events is considered. The results reveal that enhancing collaboration with a more resilient supplier can significantly improve supply chain resilience and reduce supply chain losses. It is also found that enhancing the supplier relationship can significantly benefit supply chain resilience if the collaborative intensity is relatively low, and it has less effect if supply chain members have already collaborated closely. Thus, enhancing the supplier relationship to a limited intensity is a relatively effective and economic method to strengthen supply chain resilience.

Supplier selection and order splitting modeling in the pr esence of supplier capacity and resilience

To solve the problem of a supplier＇s failure to deliver thus impacting supply chain system performance in the supply chain operating process, a model of supplier selection and order splitting in the context of a multiple sourcing setting is proposed. First, by the analysis of the elements of expected total costs of the buyer firm, namely, expected loss costs, resilience effort costs, supplier maintenance costs, and cycle purchase costs, the expected total costs function is obtained. And then, the effects of supplier characters on the supplier selection and order splitting decisionmaking are investigated by numerical examples. The results show that the maximum delivery capacity, the probability of failure to deliver and the resilience parameters are crucial elements in determining which suppliers should be selected and how to do order splitting between suppliers. Finally, current analyses focus only on the expected total costs of the buyer firm but ignore the suppliers＇ costs： thus, it is more interesting to examine the supplier decisions from both parties＇ points of view.

Comparison on neural networks and support vector machines in suppliers' selection

Suppliers＇ selection in supply chain management （SCM） has attracted considerable research interests in recent years. Recent literatures show that neural networks achieve better performance than traditional statistical methods. However, neural networks have inherent drawbacks, such as local optimization solution, lack generalization, and uncontrolled convergence. A relatively new machine learning technique, support vector machine （SVM）, which overcomes the drawbacks of neural networks, is introduced to provide a model with better explanatory power to select ideal supplier partners. Meanwhile, in practice, the suppliers＇ samples are very insufficient. SVMs are adaptive to deal with small samples＇ training and testing. The prediction accuracies for BPNN and SVM methods are compared to choose the appreciating suppliers. The actual examples illustrate that SVM methods are superior to BPNN.

k-supplier问题的贪婪近似算法

给定无向完全图G=(V,E)和正整数k,图G的顶点集V被划分为子集F和子集D=V-F.k-supplier问题主要研究如何寻找F中顶点数不多于k的子集S,使得S中的顶点到D中顶点的最大距离最小.研究了k-supplier问题,得到了一个近似比为3的多项式时间贪婪近似算法,并通过实例验证了该算法的有效性.

Infinitesimal dividing modeling method for dual suppliers inventory model with random lead times

As one of the basic inventory cost models, the （Q, τ）inventory cost model of dual suppliers with random procurement lead time is mostly formulated by using the concepts of ＂effective lead time＂ and ＂lead time demand＂, which may lead to an imprecise inventory cost. Through the real-time statistic of the inventory quantities, this paper considers the precise （Q, τ） inventory cost model of dual supplier procurement by using an infinitesimal dividing method. The traditional modeling method of the inventory cost for dual supplier procurement includes complex procedures. To reduce the complexity effectively, the presented method investigates the statistics properties in real-time of the inventory quantities with the application of the infinitesimal dividing method. It is proved that the optimal holding and shortage costs of dual supplier procurement are less than those of single supplier procurement respectively. With the assumption that both suppliers have the same distribution of lead times, the convexity of the cost function per unit time is proved. So the optimal solution can be easily obtained by applying the classical convex optimization methods. The numerical examples are given to verify the main conclusions.

Fuzzy Multi-Objective Decision Model of Supplier Selection with Preference Information

Supplier selection is a multi-objective decision problem, which must be considered many objectives, some objectives are qualitative, and others are quantitative. Meanwhile, manufacturer has preference for different suppliers. In this paper, a new multi-objective decision model with preference information of supplier is established. A practical example of supplier selection problem utilizing this model is studied. The result demonstrates the feasibility and effectiveness of the methods proposed in the paper.

Combining TOPSIS and GRA for supplier selection problem with interval numbers

Supplier selection can be regarded as a typical multiple attribute decision-making problem. In real-world situation, the values of the alternative attributes and their weights are always being nondeterministic, and as a result of this, the values are considered interval numbers. In addition, the common approach to measure the similarity between alternatives through their distance suffers from some minor shortcomings. To address these problems, this study develops a novel hybrid decision-making method by combining the technique for order preference by similarity to an ideal solution （TOPSIS） with grey relational analysis （GRA） for supplier selection with interval numbers. By introducing the intervals theory, the extensions of Euclidean distance and grey relational grade are defined. And then a new comprehensive closeness coefficient is constituted for supplier alternatives evaluation based on the interval Euclidean distance and the interval grey relational grade, which could indicate the distance-based similarity and the shape-based similarity simultaneously. A mtmerical example is taken to validate the flexibility of the proposed method, and result shows that this method can tackle the uncertainty in real-world supplier selection and also help decision makers to effectively select optimal suppliers.

An integrated model for supplier selection process

In today’s highly competitive manufacturing environment, the supplier selection process becomes one of crucial activities in supply chain management. In order to select the best supplier(s) it is not only necessary to continuously tracking and benchmarking performance of suppliers but also to make a tradeoff between tangible and intangible factors some of which may conflict. In this paper an integration of case based reasoning (CBR), analytical network process (ANP) and linear programming (LP) is proposed to solve the supplier selection problem.

Web-based supplier relationship framework using agent systems

In order to enable both manufacturers and suppliers to be profitable on today’s highly competitive markets, manufacturers and suppliers must be quick in selecting best partners establishing strategic relationship, and collaborating with each other so that they can satisfy the changing competitive manufacturing requirements. A web-based supplier relationships (SR) framework is therfore proposed using multi-agent systems and linear programming technique to reduce supply cost, increase flexibility and shorten response time. Web-based SR approach is an ideal platform for information exchange that helps buyers and suppliers to maintain the availability of materials in the right quantity, at the right place, and at the right time, and keep the customer-supplier relationship more transparent. A multi-agent system prototype was implemented by simulation, which shows the feasibility of the proposed architecture.

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.

A Model for Selecting a Biomass Furnace Supplier Based on Qualitative and Quantitative Factors

In developing countries,solar energy is the largest source of energy,accounting for 35%–45%of the total energy supply.This energy resource plays a vital role in meeting the energy needs of the world,especially in Vietnam.Vietnam has favorable natural conditions for this energy production.Because it is hot and humid,and it has much rainfall and fertile soil,biomass develops very quickly.Therefore,byproducts from agriculture and forestry are abundant and continuously increasing.However,byproducts that are considered natural waste have become the cause of environmental pollution;these include burning forests,straw,and sawdust in the North;and rice husks dumped into rivers and canals in the Mekong Delta region.Biomass energy is provided in a short cycle,is environmentally safe to use and is encouraged by organizations that support sustainable development.Taking advantage of this energy source provides energy for economic development and ensures environmental protection.Due to the abovementioned favorable conditions,many biomass energy plants are being built in Vietnam.Like other renewable energy investment projects,the selection of the construction contractor,the selection of equipment for the installation of the power plant,and the choice of construction site are complex multi-criteria decisions.In this case,decisionmakers must evaluate many qualitative and quantitative factors.These factors interact with each other and it is difficult to use personal experience to choose the optimal solution for such complex decision-making problems,especially in a fuzzy decision-making environment.Therefore,in this study,the authors use a Multi-Criteria Decision-Making(MCDM)model that uses a Fuzzy Analytic Hierarchy Process(FAHP)model and the Combined Compromise Solution(CoCoSo)algorithm to select biomass furnace suppliers utilizing both qualitative and quantitative factors.Furthermore,the results of this work will provide the first look at a hybrid CoCoSo/FAHP method that decision-makers in other fields can use to find the best supplier.

A Novel Green Supplier Selection Method Based on the Interval Type-2 Fuzzy Prioritized Choquet Bonferroni Means

In view of the environment competencies,selecting the optimal green supplier is one of the crucial issues for enterprises,and multi-criteria decision-making(MCDM)methodologies can more easily solve this green supplier selection(GSS)problem.In addition,prioritized aggregation(PA)operator can focus on the prioritization relationship over the criteria,Choquet integral(CI)operator can fully take account of the importance of criteria and the interactions among them,and Bonferroni mean(BM)operator can capture the interrelationships of criteria.However,most existing researches cannot simultaneously consider the interactions,interrelationships and prioritizations over the criteria,which are involved in the GSS process.Moreover,the interval type-2 fuzzy set(IT2FS)is a more effective tool to represent the fuzziness.Therefore,based on the advantages of PA,CI,BM and IT2FS,in this paper,the interval type-2 fuzzy prioritized Choquet normalized weighted BM operators with fuzzy measure and generalized prioritized measure are proposed,and some properties are discussed.Then,a novel MCDM approach for GSS based upon the presented operators is developed,and detailed decision steps are given.Finally,the applicability and practicability of the proposed methodology are demonstrated by its application in the shared-bike GSS and by comparisons with other methods.The advantages of the proposed method are that it can consider interactions,interrelationships and prioritizations over the criteria simultaneously.

Selection Model of Optional Parts in Suppliers Involved in New Product Development

Quality function deployment (QFD),which can translate efficiently customer requirement (CRs) into technical attributes (TAs),is widely used in new product development (NPD) as an efficient customer-driven approach. After lots of QFD application is applied in manufacturing fields,it was proved that without considering suppliers involved,it is difficult to get precise and satisfying results in each process of QFD,particularly part deployment. The paper will address the issues of a model of optional parts selection in suppliers involved in part deployment process. Further,it has been applied to an ERP system reconstruction and updating problem as an illustration.

Study on Evaluation of Supplier's Quality Assurance System

To be a worldwide competitor, enterprise needs to e va luate and select its supplier carefully. Generally, to evaluate a supplier, the evaluating effort is focused on the purchase price, delivery time, product quali ty, etc. The vendors’ quality assurance is seldom considered. However, it reflec ts the ability that a vendor can provide high quality but low cost products cont inuously and stably. In this paper, with the study on evaluation of supplier’s q uality assurance system, a set of methods and indices to supplier’s quality assu rance evaluation is introduced. The indices construct an index system, which is based on the ISO9000 series standards. According to the problem’s character and the requirement of evaluation, all the evaluation indices are set off to three k inds: general index, functional index and protective index. And the evaluation m ethod combines quantitative analysis with qualitative analysis. Firstly, a sensi tive factor model is constructed to estimate the contribution of factors that ha ve key effect on synthetic evaluation in supplier’s quality system. Then, those suppliers having low evaluating value are rejected. Secondly, fuzzy logic is int roduced to evaluate other suppliers synthetically. The rest suppliers are compar able. So, supplier’s quality assurance system can be evaluated in quantity. Afte r unification works, the evaluated suppliers can be ranked. And the best vendor can be selected out intuitively.

Supplier Evaluation Model Based on Fuzzy Measures and Choquet Integral

To identify interactions among evaluation criteria and describe their importance,a new identification method making use of a fuzzy measure is presented.The relative weight and interaction degree of every evaluation criteria pair are obtained by using the diamond pairwise comparison method.Based on comparison results,the maximum eigenvector method of analytic hierarchy process （AHP）,the hierarchical clustering method,and the phi（s） transformation are utilized to generate values of the fuzzy measure for each subset of the evaluation criterion set.Overall evaluation on each supplier is aggregated by Choquet integral with respect to the fuzzy measure.Finally,an illustrative example demonstrates the practical feasibility and validity of the proposed method.

Does supplier concentration matter to investors during the COV1D-19 crisis:evidence from China?

The literature shows that investor attention to customer–supplier disclosure increases when suppliers’information arrival is anticipated.Due to the widespread of city lockdowns in China and the implementation of social distancing to control the COVID-19 pandemic,investor attention to potential disruption of the supply chain spikes,leading to a price devaluation for firms with high supplier concentration risk.We find that a higher degree of supplier concentration is related to more serious stock price declines over the short-term and medium-term windows right after the Wuhan lockdown.This result lends support to the argument that the concentration risk of suppliers is a significant consideration for China stock market investors,especially under the potential financial distress at the firm level induced by the COVID-19 crisis.

Supplier pricing based on threshold cointegration in agri-supply chain

Aiming atthe pricing of primary agricultural products for the large-scale suppliers and the wholesalers in agri-supply chain management, an approach for the large-scale supplier pricing is presented based on the threshold cointegration method of wholesale prices online including the GBand-TAR modified Band-TAR model. Our empirical work shows that it is more appropriate for a large-scale supplier pricing with his wholesalers based on the threshold cointegration method than the conventional linear cointegration method in spatially separate markets in an agri-supply chain of soybean in China in short time. Firstly, the three pairs of prices in spatially separate markets are of long-run equilibrium and threshold cointegration. The forecast wst shows that the threshold cointegration approach is superior to the conventional linear cointegration approach in short time. Secondly, there are two thresholds of GBand-TAR in which the threshold parameters represent relative transaction costs. Larger thresholds or wider neutral band corresponds to the greater distance between markets. Thirdly, the estimation of M-TAR shows that the large-scale supplier is more sensitive to increase of wholesaler prices than decrease of wholesaler prices. The supplier can price on the forecast of market price by the threshold ECM including the GBand-TAR if the equilibrium error of threshold lag is not in the interval of thresholds in which there is not profitable trading opportunities for the supplier.

A New Decision-Making Model Based on Plithogenic Set for Supplier Selection

Supplier selection is a common and relevant phase to initialize the supply chain processes and ensure its sustainability.The choice of supplier is a multicriteria decision making(MCDM)to obtain the optimal decision based on a group of criteria.The health care sector faces several types of problems,and one of the most important is selecting an appropriate supplier that fits the desired performance level.The development of service/product quality in health care facilities in a country will improve the quality of the life of its population.This paper proposes an integrated multi-attribute border approximation area comparison(MABAC)based on the best-worst method(BWM),plithogenic set,and rough numbers.BWM is applied to regulate the weight vector of the measures in group decision-making problems with a high level of consistency.For the treatment of uncertainty,a plithogenic set and rough number(RN)are used to improve the accuracy of results.Plithogenic set operations are used to deal with information in the desired manner that handles uncertainty and vagueness.Then,based on the plithogenic aggregation and the results of BWM evaluation,we use MABAC to find the optimal alternative according to defined criteria.To examine the proposed integrated algorithm,an empirical example is produced to select an optimal supplier within five options in the healthcare industry.