Supplier selection using extended IT2 fuzzy TOPSIS and IT2 fuzzy MOORA considering subjective and objective factors

2019 ◽  
Vol 24 (12) ◽  
pp. 8899-8915 ◽  
Author(s):  
Ashoke Kumar Bera ◽  
Dipak Kumar Jana ◽  
Debamalya Banerjee ◽  
Titas Nandy
Keyword(s):  
Supplier Selection ◽  
Fuzzy Topsis ◽  
Fuzzy Moora

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.

A TODIM-Based Decision Support Framework for G-Resilient Supplier Selection in Fuzzy Environment

2016 ◽  
Vol 33 (05) ◽  
pp. 1650033 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
Siba Sankar Mahapatra
Keyword(s):  
Decision Support ◽  
Supplier Selection ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Selection Problems ◽  
Fuzzy Environment ◽  
Decision Support Framework ◽  
Application Potential

A novel decision support framework has been proposed herein to solve supplier selection problems by considering green as well as resiliency criteria, simultaneously. In this work subjectivity of evaluation criteria has been tackled by exploring fuzzy set theory. A dominance based approach has been conceptualized which is basically a simplified version of TODIM. Application potential of the proposed dominance based fuzzy decision making approach has been compared to that of fuzzy-TOPSIS, fuzzy-VIKOR and also fuzzy-TODIM. The concept of a unique performance index, i.e. “g-resilient” index has been introduced here to help in assessing suppliers’ performance and thereby selecting the best candidate. The work has also been extended to identify the areas in which suppliers are lagging; these seek further improvement towards g-resilient suppliers’ performance to be boosted up to the desired level.

scholarly journals Supplier selection using different metric functions

2015 ◽  
Vol 25 (3) ◽  
pp. 413-423 ◽  
Author(s):  
S.E. Omosigho ◽  
Dickson Omorogbe
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Topsis ◽  
Ideal Solution ◽  
Order Preference ◽  
Metric Functions ◽  
Metric Function ◽  
Topsis Technique ◽  
Intuitionistic Fuzzy Topsis ◽  
Selection Of

Supplier selection is an important component of supply chain management in today?s global competitive environment. Hence, the evaluation and selection of suppliers have received considerable attention in the literature. Many attributes of suppliers, other than cost, are considered in the evaluation and selection process. Therefore, the process of evaluation and selection of suppliers is a multi-criteria decision making process. The methodology adopted to solve the supplier selection problem is intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution). Generally, TOPSIS is based on the concept of minimum distance from the positive ideal solution and maximum distance from the negative ideal solution. We examine the deficiencies of using only one metric function in TOPSIS and propose the use of spherical metric function in addition to the commonly used metric functions. For empirical supplier selection problems, more than one metric function should be used.

Green Supplier Selection in Steel Door Industry Using Fuzzy AHP and Fuzzy MOORA Methods

2021 ◽  
Vol 10 (2) ◽  
pp. 1-11
Author(s):  
Seher Arslankaya ◽  
Miraç Tuba Çelik
Keyword(s):  
Supplier Selection ◽  
Fuzzy Ahp ◽  
Green Supplier Selection ◽  
Fuzzy Moora

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.

An integrated supplier selection approach incorporating decision maker’s risk attitude using ANN, AHP and TOPSIS methods

Kybernetes ◽  
2019 ◽  
Vol 49 (9) ◽  
pp. 2263-2284 ◽  
Author(s):  
Chunxia Yu ◽  
Zhiqin Zou ◽  
Yifan Shao ◽  
Fengli Zhang
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Evaluation Criteria ◽  
Risk Attitude ◽  
Integrated Approach ◽  
Fuzzy Topsis ◽  
Ann Model ◽  
Content Type ◽  
Selection Approach

Purpose The purpose of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the artificial neural network (ANN), analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods. Design/methodology/approach In the proposed approach, the ANN model is used to classify decision maker’s risk attitude; the fuzzy AHP method is used to determine the relative weights of evaluation criteria; and the fuzzy TOPSIS method is used to evaluate ratings of suppliers. Finally, experiments are conducted to verify the feasibility and efficiency of the proposed integrated approach. Findings Experiments results show that the proposed integrated approach is effective and efficient to help decision makers to select suitable suppliers according to their risk attitudes. Originality/value The aim of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the ANN, AHP and TOPSIS methods. The decision maker’s risk attitude toward procurement transaction is originally considered in supplier selection process.

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