Intelligent evaluation of suppliers using extent fuzzy TOPSIS method

2018 ◽  
Vol 25 (1) ◽  
pp. 259-279 ◽  
Author(s):  
Vinod Yadav ◽  
Milind Kumar Sharma ◽  
Shailender Singh
Keyword(s):  
Decision Making ◽  
Intelligent Systems ◽  
Supplier Selection ◽  
Intelligent System ◽  
Fuzzy Topsis ◽  
Vital Role ◽  
Small Scale ◽  
Quality Cost ◽  
Content Type ◽  
Selection Decision

Purpose In a developing economy like India, the contribution of small- and medium-sized enterprises (SMEs) to the national gross domestic product is significant. This sector creates immense employment opportunities and produces economic products and services. To survive in the globalized marked condition, it is essential for SMEs to be competitive on several fronts such as quality, cost, delivery, lead time, flexibility, etc. Hence, it is imperative for them to have a sound supplier base. Therefore, supplier selection problem (SSP) has a vital role to play in supply chain management of SMEs. The paper aims to discuss these issues. Design/methodology/approach However, SSP has now become a significant challenge to address due to the complexity, vagueness and various criteria involved in it. Recently, fuzzy Technique for Order Performance by Similarity to Ideal Solution method has been widely used to tackle such problems. Findings The present paper aims at developing an intelligent system for SSP, which can consider the multiple criteria and the uncertainty aspects in the decision process. A case study of a small-scale manufacturing company has been presented. Practical implications This study provides a guideline for SME sector to implement intelligent systems for supplier selection decision-making problems. Case application concludes that this model improves firm’s decision making and suppliers’ performance. Originality/value The proposed intelligent model can provide the guidelines and directions for the decision makers to effectively choose suppliers in the current competitive environment. And it also provides an opportunity for supplier improvement.

Supplier selection in agile supply chain

2016 ◽  
Vol 23 (7) ◽  
pp. 2027-2060 ◽  
Author(s):  
Chhabi Ram Matawale ◽  
Saurav Datta ◽  
S.S. Mahapatra
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supplier Selection ◽  
Partner Selection ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Agile Supply Chain ◽  
Ranking Order ◽  
Fuzzy Moora

Purpose The recent global market trend is seemed enforcing existing manufacturing organizations (as well as service sectors) to improve existing supply chain systems or to take up/adapt advanced manufacturing strategies for being competitive. The concept of the agile supply chain (ASC) has become increasingly important as a means of achieving a competitive edge in highly turbulent business environments. An ASC is a dynamic alliance of member enterprises, the formation of which is likely to introduce velocity, responsiveness, and flexibility into the manufacturing system. In ASC management, supplier/partner selection is a key strategic concern. Apart from traditional supplier/partner selection criteria; different agility-related criteria/attributes need to be taken under consideration while selecting an appropriate supplier in an ASC. The paper aims to discuss these issues. Design/methodology/approach Therefore, evaluation and selection of potential supplier in an ASC have become an important multi-criteria decision making problem. Most of the evaluation criteria being subjective in nature; traditional decision-making approaches (mostly dealing with objective data) fail to solve this problem. However, fuzzy set theory appears an important mean to tackle with vague and imprecise data given by the experts. In this work, application potential of the fuzzy multi-level multi-criteria decision making (FMLMCDM) approach proposed by Chu and Velásquez (2009) and Chu and Varma (2012) has been examined and compared to that of Fuzzy-techniques for order preference by similarity to ideal solution (TOPSIS) and Fuzzy-MOORA in the context of supplier selection in ASC. Findings It has been observed that similar ranking order appears in FMLMCDM as well as Fuzzy-TOPSIS. In Fuzzy-MOORA, the best alternative appears same as in case of FMLMCDM as well as Fuzzy-TOPSIS; but for other alternatives ranking order differs. A comparative analysis has also been made in view of working principles of FMLMCDM, Fuzzy-TOPSIS as well as Fuzzy-MOORA. Originality/value Application feasibility of FMLMCDM approach has been verified in comparison with Fuzzy-TOPSIS and Fuzzy-MOORA in the context of agile supplier selection.

Green supplier appraisement in fuzzy environment

2014 ◽  
Vol 21 (3) ◽  
pp. 412-429 ◽  
Author(s):  
Nitin Kumar Sahu ◽  
Saurav Datta ◽  
Siba Sankar Mahapatra
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Fuzzy Numbers ◽  
Content Type ◽  
Fuzzy Environment ◽  
Performance Metric ◽  
Green Performance ◽  
Selection Decision ◽  
Overall Performance ◽  
Generalized Trapezoidal Fuzzy Numbers

Purpose – In recent years, stimulated environmental awareness (green consciousness) has favored the emergence of the green supply chain paradigm. Therefore, apart from traditional supplier selection criterions, green criteria are necessarily to be incorporated in the supplier selection problem. In this context, the present study aims to highlight an efficient supplier appraisement platform by considering green performance criteria, in fuzzy environment. Design/methodology/approach – The present work exhibits an efficient fuzzy-based supplier performance assessment system using generalized trapezoidal fuzzy numbers set. A fuzzy overall evaluation index has been estimated towards assessing suppliers' green performance extent, thus facilitating supplier appraisement cum selection decision-making. Findings – The proposed method has been found efficient for solving the group decision-making problem under uncertain environment due to vagueness, ambiguity associated with decision-makers' subjective judgment. The proposed appraisement platform has been explored by an Indian automobile part manufacturing company at eastern part of India. Suppliers have been evaluated individually to check their performance level with respect to green attributes. Apart from estimating overall performance metric, the model presented here can identify ill-performing areas that necessitate future attention. Originality/value – The major contributions of this work have been summarized as follows: Development and implementation of an efficient decision-making procedural hierarchy to support suppliers' green performance extent evaluation. An overall performance metric has been introduced. Concept of generalized trapezoidal fuzzy numbers has been efficiently explored to facilitate such an appraisement cum selection decision-making. The appraisement index system has been extended with the capability to search ill-performing areas that require future progress.

The hybrid intelligent systems design using grey systems theory

2015 ◽  
Vol 5 (2) ◽  
pp. 194-205 ◽  
Author(s):  
Scarlat Emil ◽  
Virginia Mărăcine
Keyword(s):  
Systems Theory ◽  
Intelligent Systems ◽  
Explicit Knowledge ◽  
Intelligent System ◽  
Grey System Theory ◽  
Knowledge Flows ◽  
Content Type ◽  
Hybrid Intelligent Systems ◽  
Advantages And Disadvantages ◽  
Grey Systems Theory

Purpose – The purpose of this paper is to discuss how tacit and explicit knowledge determine grey knowledge and how these are stimulated through interactions within networks, forming the grey hybrid intelligent systems (HISs). The feedback processes and mechanisms between internal and external knowledge determine the apparition of grey knowledge into an intelligent system (IS). The extension of ISs is determined by the ubiquity of the internet but, in our framework, the grey knowledge flows assure the viability and effectiveness of these systems. Design/methodology/approach – Some characteristics of the Hybrid Intelligent Knowledge Systems are put forward along with a series of models of hybrid computational intelligence architectures. More, relevant examples from the literature related to the hybrid systems architectures are presented, underlying their main advantages and disadvantages. Findings – Due to the lack of a common framework it remains often difficult to compare the various HISs conceptually and evaluate their performance comparatively. Different applications in different areas are needed for establishing the best combinations between models that are designed using grey, fuzzy, neural network, genetic, evolutionist and other methods. But all these systems are knowledge dependent, the main flow that is used in all parts of every kind of system being the knowledge. Grey knowledge is an important part of the real systems and the study of its proprieties using the methods and techniques of grey system theory remains an important direction of the researches. Originality/value – The paper discusses the differences among the three types of knowledge and how they and the grey systems theory can be used in different hybrid architectures.

Sustainable circular supplier selection and evaluation in the manufacturing sector using Pythagorean fuzzy EDAS approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chang Liu ◽  
Pratibha Rani ◽  
Khushboo Pachori
Keyword(s):  
Decision Making ◽  
Human Behavior ◽  
Circular Economy ◽  
Supplier Selection ◽  
Manufacturing Sector ◽  
Uncertain Information ◽  
Manufacturing Companies ◽  
Content Type ◽  
Sustainable Supplier Selection ◽  
Selection Of

PurposeDue to stern management policies and increased community attentiveness, sustainable supply chain management (SSCM) performs a vast component in endeavor operation and production management. Sustainable circular supplier selection (SCSS) and evaluation presented the environmental and social concerns in the fields of circular economy and sustainable supplier selection. Choosing the optimal SCSS is vital for organizations to persuade SSCM, as specified in various researches. Based on the subjectivity of human behavior, the selection of ideal SCSS often involves uncertain information, and the Pythagorean fuzzy sets (PFSs) have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the multi-criteria decision-making (MCDM) procedure. Here, a framework is developed to assess and establish suitable suppliers in the SSCM and the circular economy.Design/methodology/approachThis paper introduced an extended framework using the evaluation based on distance from average solution (EDAS) with PFSs and implemented it to solve the SCSS in the manufacturing sector. Firstly, the PFSs to handle the uncertain information of decision experts (DEs) is employed. Secondly, a novel divergence measure and parametric score function for calculating the criteria weights are proposed. Thirdly, an extended decision-making approach, known as PF-EDAS, is introduced.FindingsThe outcomes and comparative discussion show that the developed method is efficient and capable of facilitating the DEs to choose desirable SCSS. Therefore, the proposed framework can be used by organizations to assess and establish suitable suppliers in the SCSS process in the circular economy.Originality/valueSelecting the optimal sustainable circular supplier (SCS) in the manufacturing sector is important for organizations to persuade SSCM, as specified in various research. However, corresponding to the subjectivity of human behavior, the selection of the best SCS often involves uncertain information, and the PFSs have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the MCDM procedure. Hence, manufacturing companies' administrators can implement the developed method to assess and establish suitable suppliers in the SCSS process in the circular economy.

scholarly journals An Approach of Interval-Valued Picture Fuzzy Uncertain Linguistic Aggregation Operator and Their Application on Supplier Selection Decision-Making in Logistics Service Value Concretion

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Muhammad Naeem ◽  
Muhammad Qiyas ◽  
Saleem Abdullah
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Multiple Criteria ◽  
Service Value ◽  
Logistics Service ◽  
Criteria Weights ◽  
Selection Decision ◽  
Interval Valued

With respect to multiple criteria group decision-making (MCGDM) problems in which both the criteria weights and the expert weights take the form of crisp numbers and attribute values take the form of interval-valued picture fuzzy uncertain linguistic numbers, some new group decision-making analysis methods are developed. Firstly, some operational laws, expected value, and accuracy function of interval-valued picture fuzzy uncertain linguistic numbers are introduced. Then, an interval-valued picture fuzzy uncertain linguistic averaging and geometric aggregation operators are developed. Furthermore, some desirable properties of the developed operators, such as commutativity, idempotency, and monotonicity, have been studied. Based on these operators, an approach to multiple criteria group decision-making with interval-valued picture fuzzy uncertain linguistic information has been proposed. Finally, a practical example of 3PL supplier selection in logistics service value concretion is taken to test the defined method and to expose the effectiveness of the defined model.

scholarly journals Construction of capital procurement decision making model to optimize supplier selection using Fuzzy Delphi and AHP-DEMATEL

2018 ◽  
Vol 25 (5) ◽  
pp. 1528-1547 ◽  
Author(s):  
Anil Kumar ◽  
Amit Pal ◽  
Ashwani Vohra ◽  
Sachin Gupta ◽  
Suryakant Manchanda ◽  
...  
Keyword(s):  
Decision Making ◽  
Automobile Industry ◽  
Supplier Selection ◽  
Selection Process ◽  
Strategic Decision ◽  
Extensive Literature ◽  
Content Type ◽  
Fuzzy Delphi ◽  
Selection For ◽  
Decision Making Model

Purpose Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. The purpose of this paper is to construct capital procurement decision-making model to optimize supplier selection in the Indian automobile industry. Design/methodology/approach To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria, although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria. Findings The results show that the total cost of ownership (TOC) is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, TOC, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier. Originality/value The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.

Selection of resilient suppliers in manufacturing industries post-COVID-19: implications for economic and social sustainability in emerging economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abhijit Majumdar ◽  
Jeevaraj S ◽  
Mathiyazhagan Kaliyan ◽  
Rohit Agrawal
Keyword(s):  
Decision Making ◽  
Incomplete Information ◽  
Emerging Economies ◽  
Supplier Selection ◽  
Fuzzy Decision Making ◽  
Ideal Solution ◽  
Fuzzy Decision ◽  
Content Type ◽  
Intuitionistic Fuzzy ◽  
Selection Of

PurposeSelection of resilient suppliers has attracted the attention of researchers in the past one decade. The devastating effect of COVID-19 in emerging economies has provided great impetus to the selection of resilient suppliers. Under volatile and uncertain business scenarios, supplier selection is often done under imprecise and incomplete information, making the traditional decision-making methods ineffective. The purpose of this paper is to demonstrate the application of a fuzzy decision-making method for resilient supplier selection.Design/methodology/approachA group of three decision makers was considered for evaluating various alternatives (suppliers) based on their performance under different primary, sustainability and resilience criteria. Experts' opinion about each criterion and alternative was captured in linguistic terms and was modelled using fuzzy numbers. Then, an algorithm for solving resilient supplier selection problem based on the trapezoidal intuitionistic fuzzy technique for order preference by similarity to ideal solution (TrIFTOPSIS) was introduced and demonstrated through a case study.FindingsA closeness coefficient was used to rank the suppliers based on their distances from intuitionistic fuzzy positive-ideal solution and intuitionistic fuzzy negative-ideal solution. Finally, the proposed fuzzy decision making model was applied to a real problem of supplier selection in the clothing industry.Originality/valueThe presented TrIFTOPSIS model provides an effective route to prioritise and select resilient suppliers under imprecise and incomplete information. This is the first application of intuitionistic fuzzy multi-criteria decision-making for resilient supplier selection.

scholarly journals An Integrated Best-Worst and Interval Type-2 Fuzzy TOPSIS Methodology for Green Supplier Selection

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 182 ◽  
Author(s):  
Melih Yucesan ◽  
Suleyman Mete ◽  
Faruk Serin ◽  
Erkan Celik ◽  
Muhammet Gul
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Fuzzy Topsis ◽  
Future Research ◽  
Negative Effects ◽  
Green Supplier Selection ◽  
Managerial Implications ◽  
Interval Type

Supplier selection is one of the most important multi-criteria decision-making (MCDM) problems for decision-makers in the competitive market. Today’s organizations are seeking new ways to reduce the negative effects they have on the environment and to achieve a greener system. Currently, the concept of green supplier selection has gained great importance for its ability to incorporate environmental or green criteria into classical supplier selection practices. Therefore, in this study, a multi-phase MCDM model based on the best-worst method (BWM) and the interval type-2 fuzzy technique for order preference by similarity to ideal solution (IT2F TOPSIS) is proposed. A case study in a plastic injection molding facility in Turkey was carried out to show the applicability of the proposed integrated methodology. The paper offers insights into decision-making, methodology, and managerial implications. Results of the case study are examined and suggestions for future research are provided.

A risk-based integrated decision-making model for green supplier selection

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1229-1252 ◽  
Author(s):  
Morteza Yazdani ◽  
Prasenjit Chatterjee ◽  
Dragan Pamucar ◽  
Manuel Doval Abad
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Supplier Selection ◽  
Potential Contribution ◽  
Effect Analysis ◽  
Content Type ◽  
Green Supplier Selection ◽  
Construction Company ◽  
Green Suppliers ◽  
Decision Making Model

Purpose Supply chain (SC) environment is surrounded by risk variables. This issue is regarded as an emerging and strategic problem which must be resolved by SC executives. The ability to measuring green supplier’s performance and affecting risk variables to demonstrating effective suppliers list has a potential contribution to be investigated. This paper aims to develop a decision-making model to assess green suppliers under legislation and risk factors. This leads to fewer disruptions in managing the SC and its impact to further improvement. It also presents research concepts forming a new approach for identification, prediction and understating relationship of supply risk. Design/methodology/approach At primal stage, different risk factors that influence green suppliers’ performance are indicated and their relationship is analyzed using decision-making trial and evaluation laboratory (DEMATEL) method. At the same time, failure mode and effect analysis is used to determine risk rating of each supplier. Finally, the evaluation based on distance from average solution (EDAS) method ranks suppliers and several comparisons and analysis are performed to test the stability of the results. The approaches include comparison to technique for order performance by similarity to ideal solution, multi-attributive border approximation area comparison, Vlse Kriterijumska Optimizacija I Kompromisno Resenje and complex proportional assessment methods, followed by analysis of rank reversal, weight sensitivity analysis and effect of dynamic metrics. Findings A real-time case study on green supplier selection (GSS) problem of a reputed construction company of Spain has been presented to demonstrate the practical aspects of the proposed method. In practice, though organizations are aware of various risks from local and global suppliers, it is difficult to incorporate these risk factors for ranking the suppliers. This real-case application shows the evaluation and incorporation of risk factors into the supplier selection model. Practical implications The proposed multi-criteria decision model quantitatively aids managers in selecting green suppliers considering risk factors. Originality/value A new model has been developed to present a sound mathematical model for solving GSS problems which considers the interaction between the supplier selection risk factors by proposing an integrated analytical approach for selecting green suppliers strategically consisting of DEMATEL, FMEA and EDAS methods.

Barriers in implementing lean manufacturing in Indian SMEs: a multi-criteria decision-making approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Piyush Jaiswal ◽  
Amit Singh ◽  
Subhas C. Misra ◽  
Amaresh Kumar
Keyword(s):  
Decision Making ◽  
Lean Manufacturing ◽  
Manufacturing Sector ◽  
New Technology ◽  
Evaluation Framework ◽  
Quality Cost ◽  
Content Type ◽  
Leadership Quality ◽  
Management Commitment ◽  
Top Management Commitment

Purpose This study aims to investigate the interrelationships among the Lean manufacturing (LM) adoption barriers in Indian SMEs. This issue has its own importance as LM has become the inescapable requirement for small- and medium-scale enterprises (SMEs) because of the increased concerns about quality, cost, delivery time and rapidly growing competition in the manufacturing sector and in India it is opposed by many factors/barriers. To act for the eradication of these barriers, we need to systematically analyze them. Design/methodology/approach Based on the available literature and consultation with the experts, the authors identified 16 LM barriers for Indian SMEs. The authors analyzed the interdependencies among the barriers and prioritized them using integrated Grey-decision-making trial and evaluation laboratory (grey-DEMATEL) approach. Findings The findings show that limited financial resources, fear in adopting new technology, lack of top management commitment and poor leadership quality are the most critical barriers for LM diffusion in Indian SMEs. Research limitations/implications The present research is based on the experts’ inputs, which may be subject to individual biases. In developing countries, such as India, geographical influences are also possible, which are neglected in this study. Practical implications This study provides significant insights that can help SMEs to focus on critical cause group barriers to accelerate the LM penetration. Originality/value The authors have proposed a Grey-DEMATEL-based LM barrier evaluation framework. Here, the authors analyze the interrelationships among the barriers for LM and segregate them in cause and effect groups.

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