Supplier Selection Method Research Articles

A comparison of fuzzy DEA and fuzzy TOPSIS in sustainable supplier selection: Implications for sourcing strategy

This paper presents a comparative analysis of the outcomes achieved when two widely applied methods for supplier selection—the ‘technique for order of preference by similarity to ideal solution’ (TOPSIS) and ‘data envelopment analysis’—are applied to the problem of identifying the most preferred sustainable suppliers. Both fuzzy DEA and fuzzy TOPSIS are applied to a common dataset of logistics service providers in Sweden. The results reveal that TOPSIS outperforms DEA in terms of both calculation complexity and sensitivity to changes in the number of suppliers. However, output rankings from the two models are found to be less than perfectly correlated. The paper concludes that utilizing both methods, as applied to just a small number of evaluation criteria and a relatively low level of detail in the data, produces a useful pooled shortlist of potential sustainable suppliers. This can then form the basis for a second stage application where either of the methods may be applied to a greater number of criteria that are specified to a higher level of detail. Even more critically, the results also have the potential to point to specific aspects for discussion when negotiating price and service quality commitments with potential sustainable suppliers.

ANALYSIS OF SUPPLIER AND DISTRIBUTOR SELECTION THEORIES OF STAPLE IN INDUSTRY (CASE STUDY: TOKO POJOK JAYA MALANG)

The purpose of this research was to obtain a model of the supplier and distributor selection method in retail management. This research is important as not many study in Indonesia has been done especially for small and big retail business. This study contains of supply chain management system at the Toko Pojok Jaya with the data collection which is carried out by using the data collection done by interview method and analyzed by qualitative descriptive technique, to find model of the best supplier and distributor selection system for retail business.

A Novel Approach for Green Supplier Selection under a q-Rung Orthopair Fuzzy Environment

With environmental issues becoming increasingly important worldwide, plenty of enterprises have applied the green supply chain management (GSCM) mode to achieve economic benefits while ensuring environmental sustainable development. As an important part of GSCM, green supplier selection has been researched in many literatures, which is regarded as a multiple criteria group decision making (MCGDM) problem. However, these existing approaches present several shortcomings, including determining the weights of decision makers subjectively, ignoring the consensus level of decision makers, and that the complexity and uncertainty of evaluation information cannot be adequately expressed. To overcome these drawbacks, a new method for green supplier selection based on the q-rung orthopair fuzzy set is proposed, in which the evaluation information of decision makers is represented by the q-rung orthopair fuzzy numbers. Combined with an iteration-based consensus model and the q-rung orthopair fuzzy power weighted average (q-ROFPWA) operator, an evaluation matrix that is accepted by decision makers or an enterprise is obtained. Then, a comprehensive weighting method can be developed to compute the weights of criteria, which is composed of the subjective weighting method and a deviation maximization model. Finally, the TODIM (TOmada de Decisao Interativa e Multicritevio) method, based on the prospect theory, can be extended into the q-rung orthopair fuzzy environment to obtain the ranking result. A numerical example of green supplier selection in an electric automobile company was implemented to illustrate the practicability and advantages of the proposed approach.

Method of Supplier Selection by Means of Correlation of Quality and Cost Characteristics of Products

Purpose: When choosing a supplier, many companies give priority to the lowest cost of products. Problems arise when the consumer wants to buy products with several better quality characteristics, but the products have only one of them. The aim is to establish a link between the quality characteristics of the product and its market value in terms of consumer benefits.Methodology/Approach: The proposed model is based on determining the importance of criteria that determine the indicators of quality, reliability, characteristics of products and their comparison with the market price at which these products are supplied to the consumer. The model is built on the basis of statistical processing of the data received from consumers about preferences at the choice of production.Findings: The method of determining the optimal supplier based on the cost and quality indicators of the product. Some indicators of the quality of products and their ranking by significance for the consumer are given. It gives the examples of calculation methods for univariate and two-factor analysis. It shows the ways of diagramming the determination of values of factors of production.Research Limitation/implication: The model is relevant only at close market value of production for the consumer.Originality/Value of paper: The methodology of criteria-based evaluation of the quality indicators of the supplied products or services allows making a selection of a products supplier on the basis of quality characteristics of the supplied products.

Intelligent decision method for supplier selection

In the process of supply chain risk management, selecting the right supplier quickly and accurately is one of the most critical issues for the company. Due to the influence of various risks, improper selection or time-consuming evaluation may lead to the company losing the best time, cost and market share. For the multi-criteria decision-making problem of supplier selection, this study proposes an intelligent method combining the combination of triangular fuzzy number and network analysis method, evaluates the alternative solutions, obtains the supplier ranking result and proves the effectiveness of the method by case studies of the electronics industry. A scientific reference is provided by this method for the development of supplier-selected intelligent systems.

A Novel Fuzzy Multi-Objective Method for Supplier Selection and Order Allocation Problem Using NSGA II

This paper introduces a supplier selection and order allocation problem in a single-buyer-multi-supplier supply chain in which appropriate suppliers are selected and orders allocated to them. Transportation costs, quantity discount, fuzzy type uncertainty and some practical constraints are taken into account in the problem. The problem is formulated as a bi-objective model to minimize annual supply chain costs and to maximize the annual purchasing value. The fuzzy weights of suppliers, which are the output of one of the supplier evaluation methods, are considered in the second objective function. Then, we propose a novel fuzzy multi-objective programming method for obtaining Pareto solutions. The method is the extension of a single-objective method exist in the literature. This method is based on the decision maker's degree of satisfaction from each fuzzy objectives considering the fulfillment level of fuzzy constraints. In the proposed method, the problem remains multi-objective and, unlike existing methods, does not transformed into a single-objective model. At the last stage of proposed method, the fuzzy results are compared with an index, and decision maker can identify the appropriate or inappropriate solutions. To solve the problem, non-dominated sorting genetic algorithm (NSGA II) is designed and computational results are presented using numerical examples.

Application of PROMETHEE method for green supplier selection: a comparative result based on preference functions

The PROMETHEE is a significant method for evaluating alternatives with respect to criteria in multi-criteria decision-making problems. It is characterized by many types of preference functions that are used for assigning the differences between alternatives in judgements. This paper proposes a preference of green suppliers using the PROMETHEE under the usual criterion preference functions. Comparable results are presented to check the effect of different preference functions on the final preference. Seven economical and environmental criteria, four suppliers and five decision makers were the main structures in the green supplier selection problem. Data were collected via personal communication with decision makers using five-point Likert scale. The algorithm of PROMETHEE under usual criterion function was implemented, and the results show that supplier A1 is the most preferred alternative. Comparative results also show that supplier A1 is the most preferred alternative despite the difference in preference functions used.

A note on Group Selection with multiple quality characteristics: power comparison of two methods

The Group Selection problem is an essential problem in the supplier selection process. The objective of the problem is to select a subset of suppliers containing the best among multiple candidate suppliers. Manufacturers should procure parts from the selected suppliers to produce high-quality products. Lin, C.J., W.L. Pearn, J.Y. Huang, and Y.H. Chen [2017. “Group Selection for Processes with Multiple Quality Characteristics.” Communications in Statistics – Theory and Methods. doi:10.1080/03610926.2017.1364392] considered the problem under multiple quality characteristics, and proposed the Modified Bonferroni method and the Multiple Comparisons with the Best (MCB) method to tackle the problem. The two methods, however, may select different subset containing the best depending on the magnitude of the differences among the k estimated index values. In this paper, we derive the power function for the Modified Bonferroni method, and compare the power of the two methods with extensive simulations. The results show that the MCB method is more powerful than the Modified Bonferroni method when the actual number of the best process is one. On the other hand, the Modified Bonferroni method significantly outperforms the MCB method when the actual number of the best process is greater than one. The results provide practitioners with useful reference about the properties of the two methods for supplier selection.

Green Supplier Selection Based on Consensus Process and Integrating Prioritized Operator and Choquet Integral

Green supplier selection, as a core part of green supply chain management, has attracted the attention of various researchers in the past decade. Plenty of green supplier selection methods based on multi-criteria group decision-making have been presented in previous literature. However, these approaches ignore the consensus level between the experts, and they rarely consider the priority level among the experts and the interdependent relationship between criteria. To handle these issues, an integrated framework of green supplier selection under the hesitant fuzzy linguistic (HFL) environment was established. In this framework, the preference information expressed by HFL was transformed into the hesitant 2-tuple linguistic (H2TL). Then, the consensus process was introduced into the green supplier selection process to increase the consensus level between experts. The H2TL prioritized operator and Choquet integral operator were respectively applied to construct the group decision matrix and derive the ranking order of green suppliers. Finally, we used a numerical example to demonstrate the validity and applicability of the presented framework and implemented a comparative analysis to highlight the features of the presented method.

Power analysis for group supplier selection with multiple production lines

AbstractGroup supplier selection problem is a critical problem because outsourcing is an important issue for supply chain management. For the advanced production processes with extremely low fraction of defectives, typical supplier selection methods no longer work because any sample of reasonable size probably contains no defective items. Thus, process capability indices have been extensively used for advanced production processes to evaluate and measure whether the process meets the specifications and they also provide quality assurance. In the globally competitive production environment, processes involving multiple production lines are quite common due to economies of scale considerations. In this paper, we consider a group supplier selection problem for multi‐supplier and multi‐line, in which a supplier group containing the best suppliers is selected based on a multi‐line yield index . To avoid the inflation of multiple comparisons, we apply the Bonferroni method and subtraction test statistic to tackle the group supplier selection problem. Critical values for testing procedure and required sample sizes for designated selection powers are obtained and tabulated. In addition, we apply multiple comparisons with the best method and compare the selection powers with the Bonferroni method for various power settings to provide more accurate group supplier decisions for real‐world applications.

Pengambilan Keputusan Multi Kriteria: Kajian Teoritis Metode dan Pendekatan Dalam Pemilihan Pemasok

This article attempts to explore and review methods and approaches in the Supplier selection process. Review of articles related to the approach in supplier selection that includes identification, evaluation and contract activities with suppliers is reviewed based on the quantitative and qualitative models conducted in this article. In this article, a discussion of supplier selection methods previously investigated by researchers is done through literature review published in several reputable journal database. 86 journal articles successfully collected and reviewed related methods and approaches used by researchers in memeilih supplier. From the results of this study can be concluded that the method of supplier selection through qualitative and quantitative approach is then subdivided into 4 categories with 18 methods discussed.

Modularity as a support for frugal product and supplier network co-definition under regional market constraints: a mirroring hypothesis application

Creating new products or adapting existing ones to fit with specific customer requirements from regional as well as emerging markets is a challenging issue for competitive companies that work to maintain acceptable market share rates. Besides the importance of providing original solutions tailored to the target market characteristics, companies should consider their production strategy as a key factor for reaching frugality objectives under regional constraints. The co-evolution of product and production network aims to provide a concurrent design and management of product architecture, local production systems, and OEM–suppliers relationships. This paper proposes a modular-based approach as an application of the mirroring hypothesis for supporting the co-definition of product structure and supplier network. Supplier selection and evaluation method for frugal innovation perspective is proposed as a key part of the proposed approach and applied in an industrial use case for validation.

A zöld ellátási lánc vizsgálati módszerei, különös tekintettel a beszállítói kiválasztás és értékelés eszközeire

Today, more and more articles have emerged in the field of sustainability and sustainable development. Sustainability plays an important role in supply chain management too. Green Supply Chain Management (GSCM) has emerged as a key approach for enterprises seeking to make their businesses environmentally sustainable. The notion of GSCM implies the insertion of environmental criteria within the decision-making context of the traditional supply chain management. Enterprises are increasingly expected to extend their sustainability efforts beyond their own operations to their suppliers and customers to their sustainability expectations. Literature of green supplier evaluation and selection methods number is large, though the number of environmental factors are relatively limited. Recently in supply chain management decision making, approaches for evaluating green supplier performance have used both qualitative and quantitative environmental data. Given this evolving research area, the purpose of this article is to analyse research conducted in international scientific journals focusing on the selection and evaluation of a green supplier. The purpose of this article will answered two questions: Which selection methods are commonly used? What environmental and other selection criteria for green supplier management are popular?

Application of Multi-Criteria Decision-Making Methods for Supplier Selection in an Agricultural Enterprise

In today's turbulent market conditions, the selection of suppliers in an agricultural enterprise constitutes a primary function, and the entire supply chain with the necessary raw materials and intermediate goods plays an important role in the day-to-day functioning of the economic entity in this field. In order to successfully solve the problem of choosing a supplier, the decision maker uses the methods of multi-criteria analysis, and the corresponding software support. The subject of research in this paper is the selection of mineral fertilizer suppliers in the agricultural enterprise using the AHP methodology, which is one of the most commonly applied methods of multi-criteria analysis today. The aim of the research is to rank suppliers on the basis of the set criteria, and a supplier with the highest rating was selected for the supplier of mineral fertilizer as the observed enterprise.

Supplier selection considering sustainability measures: an application of weight restriction fuzzy-DEA approach

With the growing of consumer awareness in environmental and social issues sustainable development has become an essential element in supply chain management. Supplier evaluation and selection is one of the main strategic decisions for purchasing management in supply chain. This paper use Data Envelopment Analysis (DEA) to propose a new model for evaluation and ranking of a given set of suppliers from sustainable point of view. The proposed model integrates the fuzzy set theory and DEA to consider the decision makers’ preferences and handle the ambiguity and uncertainty in supplier selection process. For this purpose, linguistic values in the form of triangular fuzzy numbers are used to assess the weights of criteria, sub-criteria, and the ratings of suppliers’ performance with respect to sub-criteria. Then, a fuzzy-DEA model, using α-cut approach, is developed considering weight constraints. An application from Supplying Automotive Parts Company (SAPCO) Company, which is one of the largest suppliers of automotive parts in the Middle-East, is presented to show the applicability of the proposed model. Finally, the proposed weight restriction fuzzy-DEA model is validated through comparing with one of the recent supplier selection methods.

A QFD-ANP Method for Supplier Selection with Benefits, Opportunities, Costs and Risks Considerations

This paper presents an original integrated procedure to evaluate and select suppliers for purchasing decisions. The procedure exploits the quality function deployment approach to define the suppliers’ characteristics, coupled with the analytic network process to capture the interrelations among the selection criteria and integrated with a benefits, opportunities, costs and risks (BOCR) analysis. As such, the proposed approach is more structured than the existing methods for supplier selection; in particular, it allows simultaneously to take into account the relevant criteria for supplier selection, to capture the situation in which the decision criteria are somehow dependent on one another and to evaluate the positive and negative aspects of the selection process. By using the proposed approach, companies can derive useful information to guide their partner selection process. An extensive case study is reported to show the application of the model to a selection process of a real Italian company. The application shows that the model is effective in identifying the most suitable supplier; moreover, a detailed sensitivity analysis highlights that the results of the ranking are very robust against possible changes in the relative importance of the BOCR perspectives.

An integrated fuzzy MOORA method and FMEA technique for sustainable supplier selection considering quantity discounts and supplier's risk

Abstract Supplier selection is a complex process and plays a signification role in promoting the sustainable supply chain. In this study, a fuzzy multi-objective optimization model based on the ratio analysis (fuzzy MOORA) is applied to evaluate the supplier's overall performance. In reality, suppliers face risks like natural calamity or political variability. Hence, failure mode and effects analysis (FMEA) is implemented to evaluate the risks of a supplier. Moreover, a novel multi-objective mathematical model is developed to consider supplier's sustainability and order allocation simultaneously. The efficiency and applicability of the proposed approach is shown by a case study of the evaporative cooler in the home appliance industry. The current approach can be implemented in many manufacturing industries such as electrical, automotive and chemical. The results show that by employing the proposed model not only potent to increase total profit but also decrease the amount of risks which imposes on the sustainability.

Selecting the Right Suppliers in Procurement Process along Supply Chain-a Mathematical Modeling Approach

AbstractProcurement management is a function for B2B market and a complex concept based on a continuous buying cycle and supposes: determining the need, taking the decision of buying, identification of sources, selecting and choosing the right suppliers, contracting, and maintaining the relationships with the future contractors.Supplier selection is a challenging task along supply chain and is based on some important criteria in order to choose the right supplier and maintain with it a long and prosper relationship. In order to select the right supplier, the buyer may use quantitative and qualitative methods. In this article we present the importance of supplier selection along supply chain and the used criteria to do this. We also present a supplier selection method based on mathematical models, especially on regression function and time series analysis, in order to show that they bring important benefits for the companies which used them.

Inventory-related costs in green supplier selection problems with Data Envelopment Analysis (DEA)

In today's competitive and dynamic world, the importance of supplier evaluation has become more widely recognized. When considering measurement of supplier performance and supply impact the literature identifies two sets of criteria: management criteria and green criteria. Management criteria can be extended with process cost criteria, which then poses new requirements to be met by the evaluation methodologies. This paper aims to present a methodology that can handle the different characteristics of these criteria. As a solution, a green supplier selection problem is generalized.A Data Envelopment Analysis (DEA)-type supplier selection method was developed, where green factors served as the output variables of a DEA model, and management variables were the inputs. This new methodology examines, in addition to managerial and green criteria, the effect of inventory-related costs, such as the EOQ costs of inventory holding or ordering costs on the selected supplier. The parametrical linear programming of technological coefficients is used in the DEA method. This paper draws attention to a new problem, namely, the literature fails to provide solutions for how to handle the nonlinearity of the cost functions in the most commonly used methodologies.

An analytical closed-form solution for multiple line supplier selection problem

Supplier selection is an essential issue, particularly, for semiconductor manufacturing. Nowadays, since high demands in the globally competitive semiconductor manufacturing environment, multiple-line processes are quite commonly applied. In the paper, we consider a two-stage method composing of quality verification and selection decision for multiple-line supplier selection problems. Since quality performance is an important criterion in supplier selection, we test whether the new supplier has a significantly better capability than the existing supplier based on the multiple-line yield index in the stage of quality verification. In selection decision, when the magnitude of capability outperformance is significant, switching contracts to a new entrant supplier is suggested. In addition, analytical closed-form solutions for asymptotical critical values and required sample sizes are derived and tabulated for the investigated multiple-line supplier selection problem. We demonstrate the applicability of the proposed supplier selection method by presenting a real-world example taken from a semiconductor packaging shop floor located in the Science-based Industrial Park in Hsinchu, Taiwan.