Supplier Selection Problem Research Articles

Application of Fuzzy-TOPSIS Method in Supporting Supplier Selection with Focus on HSE Criteria: A Case Study in the Oil and Gas Industry

Supply chain management is an emerging topic in the oil and gas industry. There is higher exposure of contractors to undesirable incidents and supplier selection is a multicriteria decision problem (MCDM). A fuzzy-TOPSIS method was employed in the evaluation of three suppliers regarding four HSE criteria. This method was applied in a case study of the oil and gas industry involving a contractor bidding process. Results reinforced that fuzzy-TOPSIS is a versatile and suitable method for supplier selection problems, with low computational complexity and promoting a better user experience. This method contributes to greater effectiveness and agility in the selection processes of suppliers regarding HSE management. The fuzzy-TOPSIS model is suitable for supplier selection problems and some of the benefits of applying this method are that it allows the attribution weights according to the level of importance of each criterion and considers the complexity, subjectivity, and uncertainty of the decision process. One has determined that it was essential to have a robust and consistent process for weighting the criteria and defining the most appropriate linguistic variables.

Extended TODIM method based on VIKOR for q‐rung orthopair fuzzy information measures and their application in MAGDM problem of medical consumption products

Nowadays, supply chain management (SCM) has achieved considerable attention from all over the world. q-rung orthopair fuzzy set, developed by Yager, is the entirety of the most prominent tool to express fuzzy data in the decision-making problems. In this study, the introduction of two new generalised measures (entropy and Jensen–Tsalli divergence measure) of q-rung orthopair fuzzy information involving one real parameter is given. The proposed measures have satisfied all the necessary mathematical properties of being a measure. Then the introduced entropy and divergence measure is used to obtain the objective weights. Based on the proposed entropy and divergence measure, we proposed a new decision method to deal with multiple-attribute group decision-making problems under the q-rung orthopair fuzzy environment. Then, on the basis of the TODIM and VIKOR techniques, an integrated TODIM-VIKOR approach is developed to solve multiattribute group decision-making problem. In this paper, TODIM aims to determine the overall dominance degree and VIKOR aims to determine the compromise solution. Lastly, we handle a supplier selection problem to verify the performance of the proposed q-rung orthopair fuzzy TODIM-VIKOR method and results explore the reliability and effectiveness of our proposed methodology by comparing the ranking solution with the ranking results of the existing approaches.

Evaluating Suppliers for Healthcare Centre using Ordinal Priority Approach

Supplier selection is one of the most critical problems in the industry. In the healthcare sector, where the tolerance level for mistakes and errors is low, the need to improve the supplier evaluation system is ever increasing. Earlier, the cardinal data-based mathematical models played an important role in supplier selection however since last few decades, the emphasis on the decision-making methods that can handle ordinal relations is gaining exceeding attention. The development of the Ordinal Priority Approach (OPA) is an essential milestone in this regard that is being used in the current study to evaluate the suppliers of a Chinese healthcare facility. The study confirms that the OPA is convenient and powerful approach that can single-handedly estimate the weights of suppliers, criteria and experts. The results demonstrated the feasibility and validity of the approach for healthcare supplier selection problems.

A step-up approach for selecting substitute suppliers under nonlinear profile data

ABSTRACT Selecting qualified suppliers from a group of candidates is important to procurement. Having several qualified suppliers to choose from can increase production flexibility and bargaining power. This research aims at selecting the substitute suppliers that can produce the parts with the same quality as the current supplier. Most of the existing supplier selection methods focused on univariate or linear profile data, which are insufficient to solve the supplier selection problem under nonlinear profile data. This research develops a step-up approach to select qualified suppliers for substitution under nonlinear profile data where there exists a nonlinear functional relationship between the quality characteristic and the explanatory variable. The proposed approach uses polynomial regression followed by the sequential test procedure to compare profile differences. The simulation results show that the proposed approach can reject the suppliers with different profile functions from the current supplier with satisfying power levels. To illustrate the effectiveness and practicality, the proposed approach is applied to select qualified voice coil motor (VCM) suppliers for a digital camera module manufacturer. Procuring the VCM from the selected suppliers can fulfill a higher demand, while maintaining the operational function and quality of the digital camera module.

An integrated decision-making approach for sustainable supplier selection in the chemical industry

Due to an increased awareness of ecological protection and resultant stringent legislations, business organizations are highly motivated to improve the sustainable performance of their supply chain in order to achieve sustainable development goals. The chemical industry is a high-risk, high-pollution, and high-efficiency industry, that would benefit from a systematic and sustainability focused evaluation system for supplier selection. Yet, to date, few studies have conducted the necessary in-depth analysis of the characteristics of this industry from the economic, social, and environmental perspectives. Despite the many methods and models that have been proposed to resolve the sustainable supplier selection (SSS) problem, no research has yet considered the different characteristics of each triple bottom line dimension. Accordingly, this paper addresses this problem by proposing a hybrid multi-method and multi-criteria decision-making framework for SSS in the chemical industry. Based on specific characteristics of the chemical industry, this study applies Fuzzy Grey Relational Analysis (FGRA), Failure Mode and Effects Analysis (FMEA), and cloud computing-entropy weight method (EWM) to analyze the economic, social, and environmental dimensions, respectively. Finally, this study integrates the evaluation results of the three dimensions using the Decision-making Trial and Evaluation Laboratory (DEMATEL). The proposed approach and decision-making model can help managers of sustainable supply chains in the chemical industry to choose more sustainable suppliers, respond to market demands quickly, and maintain high competitiveness in the market. An illustrative application of the proposed framework and model is undertaken in one of the biggest Chinese petrochemical companies to verify its practicality and reliability.

The New Fuzzy Analytical Hierarchy Process with Interval Type-2 Trapezoidal Fuzzy Sets and Its Application

The degree of type-1 fuzzy sets membership function cannot express the linguistic variable of a complex problem. The type-2 fuzzy sets as a problem solver such that more fuzziness for constructing membership functions can be handled. Recently, many multi-criteria decision making (MCDM) methods have been expanded using type-2 fuzzy sets. Analytical Hierarchy Process (AHP) is one of the well-known MCDM that can take into account multiple and conflicting criteria at the same time. Our goal is to develop an interval type-2 trapezoidal fuzzy AHP through the new proposed ranking i.e. the modified total integral value. Based on the illustrative examples for trapezoidal type-2 fuzzy sets, the new proposed ranking has a well-performance in ranking. Furthermore, we apply the new trapezoidal type-2 fuzzy AHP to a supplier selection problem. Based on the results of the application, the new fuzzy AHP has the same ranking results as the existing fuzzy AHP.

Ambalaj Tedarikçi Seçim Probleminin Çözümü İçin Hibrit Çok Kriterli Bir Karar Verme Yöntemi Önerisi

Selection or evaluation problems are solved by looking at the different performance factors of the suppliers along the supply chain and by making comparisons with each other, and it is ensured that important preliminary information about the suppliers is obtained. This study has been prepared in order to choose the most suitable supplier among the suppliers that provide / are candidates to provide packaging material for an enterprise producing goodsDecision processes may not always have precision due to differences of opinion arising from human behaviour. When supplier selection problems are solved, many criteria, such as different opinions of decision-makers and their conflict of interests are considered. Multi-Criteria Decision Making (MCDM) techniques are highly effective in finding solutions to such problems. The goal of this article was to find a solution to packaging supplier selection problem of a manufacturing company in a fuzzy environment. To this end, eight suppliers were examined in line with 15 evaluation criteria. The opinions of 4 different decision-makers were taken during decision-making process. The solution of the problem was based upon a mixed model consisting of Fuzzy Analytic Hierarchy Process (F-AHP), used to determine the weights of the criteria, and Fuzzy Weighted Aggregated Sum Product Assessment (F-WASPAS), utilised to make preference among alternatives. At the end of the analysis on the determination of the criteria weights, the most appropriate supplier selection was determined as the delivery date and price, respectively, the two factors most influencing the construction phase. As a result of the evaluation made, A2 was specified to be the most proper supplier. Sensitivity analysis was performed to identify the effectiveness of the results. A2 was determined to be the most proper supplier according to the selection results obtained by MARCOS, MABAC, SAW, ARAS, TOPSIS, EDAS methods.

A NOVEL APPROACH FOR GREEN SUPPLIER SELECTION PROBLEM: FUZZY AXIOMATIC DESIGN WITH RISK FACTORS

Today’s environmental conscious world forces companies to be more about energy and water consumption. New trends in the world generally provide competitive advantage to the firms if they work on environmental issues. As a critical decision of companies, supplier selection problem needs to consider the environmental factors and economical factors simultaneously. This study proposes a novel solution methodology for green supplier selection problem: Fuzzy axiomatic design with risk factors. This method is applied in many decision-making problems in the literature successfully. A case study is presented to implement the method and the results are compared with traditional fuzzy axiomatic design and fuzzy TOPSIS. It has seen that the decision of the best supplier selection can be influenced by the risk factors such as the deviation in the economical conditions or the working conditions of the company.

Optimizing the Combined Problem of Facility Location and Multi-Objective Supplier Selection Using a Comprehensive Benchmarking Method

초록·키워드 목차 오류제보하기 The selecting suppliers is one of the most important decisions in any supply chain, which, if properly selected, will reduce the costs of supply chain production. On the other hand, in a company"s logistics decisions, facility location has a great impact on supply chain design. Therefore, in this study, the facility location problem, supplier selection and order allocation in a multi-cycle and multi-product supply chain is studied in which economic goals and network reliability are considered as a two-objective optimization / decision-making problem. To evaluate the mathematical model, the model has been implemented in GAMS software by LP metric method with different P values. Because of solving the mathematical model, the selected location of the facility, the best suppliers to purchase products and the optimal allocation to each supplier are determined. The results show that the LP metric method has a good performance in finding optimal solutions to the problem and can be efficient in searching for optimal solutions. #Supplier Selection #Facility Location #Multi-Objective Mathematical Model #LP Metric Method ABSTRACT1. INTRODUCTION2. PROBLEM STATEMENT AND MATHEMATICAL MODEL3. SOLUTION METHOD4. RESULTS5. CONCLUSIONREFERENCES

“A multi-tier sustainable food supplier selection model under uncertainty”

Supplier selection in food supply chains (FSCs) is not much explored due to the inherent difficulties, complexities and nature of food industry. Food security and quality are top row topics in today’s world health scenario. During sudden food crisis, it needs extra attention where producers, suppliers, and stakeholders play the most vital roles. This paper puts forward a two-phase sustainable multi-tier supplier selection model for FSC based on an integrated decision analysis under multi-criteria perspectives considering sustainability criteria, suppliers and sub-suppliers. In the first phase, the model estimates supplier selection criteria weights using a combined version of step-wise weight assessment ratio analysis (SWARA) and level based weight assessment (LBWA) in conjunction with D-numbers. In the second phase, Measurement of Alternatives and Ranking according to the COmpromise Solution (MARCOS)-D method is applied to obtain a ranking pre-order of different tier suppliers. Moreover, several sensitivity analyses are carried out in order to examine model reliability. To check application practicability, the proposed model is implemented in a case study of WineSol Corporation in Spain. The proposed model is expected to serve as a kickoff point for developing advanced decision-making models for effectually address multi-tier supplier selection problems under uncertain environment.

The study of multi-objective supplier selection problem by a novel hybrid method: COA/ε-constraint

Today, paying attention to the interests of suppliers in supply chain management strategies is one of the important points in the success of long-term and strategic relationships with suppliers. Not paying enough attention to these points sometimes causes irreparable damage to the overall structure of the organization. In response to this need, researchers have developed and proposed different models according to different approaches. This research has presented a special model with the approach of answering these problems. This approach, which is based on the cuckoo optimization algorithm (COA), can solve the problems in multi-objective methods in addition to single-objective problems. This method based on the COA and the e-constraint method named COA/e-Constraint. The general approach of this method is to turn a multi-objective problem into a single-purpose problem, which is associated with increased efficiency. The model studied in this paper, with the aim of creating coordination between buyers and suppliers in the problem of supplier selection, is a three-objective model of cost, quality and delivery time, which is implemented to evaluate the performance of the proposed method. The results show the superiority of the proposed method over similar approaches in terms of creating a Pareto frontier.

A new Pythagorean fuzzy-based decision-making method through entropy measure for fuel cell and hydrogen components supplier selection

While fuel cell combined with hydrogen (FCH) technology is still largely in its infancy striving to find its footing, the present market stage towards commercialisation is bridged by the pervasive research and development (R&D) and innovation. Providing spare parts and auxiliary components of the FCH systems plays a significant role in advancing the process. For the successful transition, an optimal supplier selection function can flourish the long-term research, and further, address the lack of technological knowledge to manufacture high performance and affordable components. This paper presents an integrated approach based on entropy, Step-wise Weight Assessment Ratio Analysis (SWARA) and Complex Proportional assessment (COPRAS) methods under the Pythagorean fuzzy environment for the FCH supplier selection. In this method, the criteria weights were first calculated by combining the objective weights determined by the entropy-based approach and the subjective weights by the SWARA method. For this purpose, a new entropy measure was proposed through the Pythagorean fuzzy set as one of the new flexible tools to handle the uncertain and inaccurate information arisen in complex MCDM problems. An integrated approach developed in this study can overcome the insufficiencies which arise either in an objective-weighting model or a subjective-weighting model. COPRAS was then utilised to evaluate the ranking order of the alternatives. A real-world case study of the FCH components supplier selection problem was considered to implement the proposed integrated approach. Finally, a comparison and sensitivity analysis were discussed to illustrate the usefulness of the proposed method.

A Decision-Making Approach Based on New Aggregation Operators under Fermatean Fuzzy Linguistic Information Environment

Fermatean fuzzy linguistic (FFL) set theory provides an efficient tool for modeling a higher level of uncertain and imprecise information, which cannot be represented using intuitionistic fuzzy linguistic (IFL)/Pythagorean fuzzy linguistic (PFL) sets. On the other hand, the linguistic scale function (LSF) is the better way to consider the semantics of the linguistic terms during the evaluation process. It is worth noting that the existing operational laws and aggregation operators (AOs) for Fermatean fuzzy linguistic numbers (FFLNs) are not valid in many situations, which can generate errors in real-life applications. The present study aims to define new robust operational laws and AOs under Fermatean fuzzy linguistic environment. To do so, first, we define some new modified operational laws for FFLNs based on LSF and prove some important mathematical properties of them. Next, the work defines several new AOs, namely, the FFL-weighted averaging (FFLWA) operator, the FFL-weighted geometric (FFLWG) operator, the FFL-ordered weighted averaging (FFLOWA) operator, the FFL-ordered weighted geometric (FFLOWG) operator, the FFL-hybrid averaging (FFLHA) operator and the FFL-hybrid geometric (FFLHG) operator under Fermatean fuzzy linguistic environment. Several properties of these AOs are investigated in detail. Further, based on the proposed AOs, a new decision-making approach with Fermatean fuzzy linguistic information is developed to solve group decision-making problems with multiple attributes. Finally, to illustrate the effectiveness of the present approach, a real-life supplier selection problem is presented where the evaluation information of the alternatives is given in terms of FFLNs. Compared to the existing methods, the salient features of the developed approach are (1) it can solve decision-making problems with qualitative information data using FFLNs; (2) It can consider the attitudinal character of the decision-makers during the solution process; (3) It has a solid ability to distinguish the optimal alternative.

Sustainable Supplier Selection and Order Allocation Under Risk and Inflation Condition

The main objective of this paper is to develop an integrated multiobjective and multiperiod mathematical model for sustainable supplier selection and order allocation of an automotive manufacturer. In spite of the vast quantity of research on this area, integrated consideration of risk and inflation in sustainable supplier selection and order allocation problem is less investigated. To fill this gap, this paper aims to develop a multiobjective sustainable supplier selection and order allocation model considering risk and inflation. Particularly, six objective functions of total cost, economic score, environmental score, social score, inflation rate, and risk level along with related constraints are optimized in the model. The developed model is solved using weighted sum approach and augmented ε-constraint method. In addition, a sensitivity analysis has been conducted. The results provide the best sustainable suppliers and the optimum quantity of products to be purchase from each supplier in each period.

Integration of AHP-MOORA Algorithm in Green Supplier Selection in the Indonesian Textile Industry

In selecting suppliers, one approach that can be used to solve this problem is Multi-Criteria Decision Making (MCDM). MCDM involves several criteria with both quantitative and qualitative assessments. This research attempts to solve the Green Supplier Selection (GSS) problem by using the integration of Analytical Hierarchy Process (AHP) and Multi-Objective Optimization On The Basis Of Ratio Analysis (MOORA). AHP is used as the weighting of the GSS criteria and sub-criteria. Furthermore, MOORA is used to rank the best suppliers. This research was conducted in the textile industry in Indonesia. Eight criteria and 15 sub-criteria GSS are used to select eight suppliers. The results show that the product price has the most excellent weight in supplier selection. In addition, the AHP-MOORA method can be used in solving GSS problems.

Circular intuitionistic fuzzy TOPSIS method with vague membership functions: Supplier selection application context

The membership function of a general type-2 fuzzy set is three-dimensional in order to incorporate its vagueness through the third dimension. Similarly, Circular intuitionistic fuzzy sets (CIFSs) have been recently introduced by Atanassov (2020) as a new extension of intuitionistic fuzzy sets, which are represented by a circle representing the vagueness of the membership function. CIFSs allow decision-makers to express their judgments including this vagueness. In this study, the TOPSIS method, which is one of the most used multi-criteria decision-making methods is extended to its CIF version. The proposed CIF-TOPSIS methodology is applied to the supplier selection problem. Then, a sensitivity analysis based on criteria weights is conducted to check the robustness of the proposed approach. A comparative analysis with single-valued intuitionistic fuzzy TOPSIS method is also performed to verify the developed approach and to demonstrate its effectiveness

An extended framework to evaluate sustainable suppliers in manufacturing companies using a new Pythagorean fuzzy entropy-SWARA-WASPAS decision-making approach

PurposeThe purpose of this study to introduce a new extended framework to evaluate and rank the sustainable suppliers based on the different sustainable criteria in the manufacturing companies using a new fuzzy decision-making approach.Design/methodology/approachThis paper introduces a new approach using decision-making and Pythagorean fuzzy sets (PFSs) to assess the best sustainable supplier. To doing so, this study integrated the entropy, stepwise weight assessment ratio analysis (SWARA) and weighted aggregates sum product assessment (WASPAS) methods under PFSs. To calculate the criteria weights, the combined entropy-SWARA method is used to compute the objective weight and subjective weight, respectively. Furthermore, the WASPAS model is utilized to rank sustainable supplier alternatives.FindingsThe results of the analysis found that occupational health and safety systems had the highest rank among other criteria, followed by green product and eco-design, green R&D and innovation and green technology. In addition, the findings of the paper demonstrated that the extended approach was efficient and useful for selecting and evaluating the best sustainable supplier in the manufacturing companies.Originality/valueRecent years have witnessed a number of studies aimed at incorporating the sustainability standards into the supplier selection problem; however, only a little research has been conducted on developing a fuzzy method for decision-making in a manner to assess and choose suppliers with high sustainability in the insurance market, encompassing the three above-mentioned sustainability criteria.

A GREY HYBRID MODEL TO SELECT THE OPTIMAL THIRD-PARTY LOGISTICS PROVIDER

Enterprises need to work with a proper third-party logistics provider to reduce costs and increase their logistics performance; so the third-party logistics (3PL) provider selection problem is a significant one for them. In this study, grey step-wise weight assessment ratio analysis (SWARA) and grey combinative distance-based assessment (CODAS) are proposed to address this problem. To the best of the authors’ knowledge, no other study uses grey SWARA and grey CODAS together to solve any problem. Therefore a new grey hybrid model incorporating grey SWARA and grey CODAS is proposed to identify the best 3PL provider.

Multi-objective model for supplier selection and order allocation problem with fuzzy parameters

Disasters, such as Coronavirus pandemic and Japan’s earthquake and tsunami, negatively hits firms and markets. It may drastically increase market demand for some products, or decrease suppliers’ ability to supply them at right quantity, quality and time. This uncertainty can be modeled with the fuzzy set theory that is less data-demanding than the probability theory. When a supplier selection problem (SSP) is formulated by fuzzy mathematical programming technique, we have to address two issues: (1) fuzzy constraints, due to the uncertainty in demand and supply capacity, and (2) fuzzy coefficients, due to the uncertainty in defective and late delivery rates, etc. In this study, we develop a fuzzy multi-objective model for a SSP to address these two issues. We first develop a weighted additive function to transform the fuzzy multi-objective model to a fuzzy single-objective model that can effectively consider the decision makers’ preferences. Then, a resolution method is applied to solve the single-objective model with fuzzy parameters.

An approach for supplier selection problem based on picture cubic fuzzy aggregation operators

This article is an advanced approach to picture fuzzy set through the application of cubic set theory. For instance, we establish the idea of the picture cubic fuzzy sets (PCFSs) theory and define several operations for PCFS. Also, presented some weighted aggregation operators under picture cubic fuzzy information, so called picture cubic fuzzy weighted averaging (PCFWA) operator, picture cubic fuzzy order weighted averaging (PCFOWA) operator, picture cubic fuzzy weighted geometric (PCFWG) operator, and picture cubic fuzzy order weighted geometric (PCFOWG) operator. Further, we study their fundamental properties and showed the relationship among these aggregation operators. In order to determine the feasibility and practicality of the mentioned new technique, we developed multi-attribute group decision -making algorithm with picture cubic fuzzy environment. Further, the developed method applied to supply chain management and for implementation, consider numerical application of supply chain management. Compared the developed approach with other preexisting aggregation operators, and we concluded that the defined technique is better, reliable and effective.