Evaluation and Selection of Green Suppliers Using Fuzzy VIKOR and Fuzzy TOPSIS

2019 ◽  
pp. 202-218 ◽  
Author(s):  
Sasikumar P. ◽  
Vimal K. E. K.
Keyword(s):  
Manufacturing Industry ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Fuzzy Vikor ◽  
Evaluation Approach ◽  
Fuzzy Environment ◽  
Environmental Image ◽  
Green Suppliers ◽  
Case Organization

Green supplier selection is considered to be one of the prominent strategic ways to determine the success of whole supply chain in recent times. In this chapter, fuzzy VIKOR and fuzzy TOPSIS methods are used to select the suitable green supplier under fuzzy environment. The green supplier evaluation approach is demonstrated with a real-world case study involving textile manufacturing industry in southern part of India concerning 11 foremost evaluation criteria that the company has determined to select the most suitable supplier. The compromising solution for the four decision makers in Fuzzy VIKOR corroborate with the compromising solution of Fuzzy TOPSIS method. The application of proposed method in the case organization helps to identify the appropriate supplier systematically. The result offer useful insight for the managers to select the suitable supplier to improve the environmental image of the organization.

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.

Implementation of green supplier development process model in Indian automobile industry

2018 ◽  
Vol 29 (5) ◽  
pp. 938-960 ◽  
Author(s):  
Shivangi Viral Thakker ◽  
Santosh B. Rane
Keyword(s):  
Automobile Industry ◽  
Process Model ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Supplier Development ◽  
Journal Articles ◽  
Content Type ◽  
Automobile Components ◽  
Green Suppliers

Purpose The purpose of this paper is to develop a green supplier development (GSD) process model and validate the model with a case study in Indian automobile industry. Design/methodology/approach A literature survey of peer-reviewed journal articles, survey reports and paradigmatic books with managerial impact is done for the research. The process of GSD is modeled using stage-gate approach and KPIV and KPOV of the process are determined. The process model is implemented in an Indian automobile components manufacturing industry for validation. Findings The industry implemented the model with ten suppliers and was able to successfully convert seven of them into Green suppliers. Remaining three suppliers were asked to repeat the process again or terminate the contracts. Model implementation took around three years starting from planning of resources and finances to actual development of suppliers. Research limitations/implications The model implementation was done with a small automobile industry and hence the validation and implications may be generalized by taking the case study further in different industries. It would be beneficial to test the model with case studies of large-scale industries. Practical implications The process model for implementing GSD activities will help managers in taking complex investment decisions. The stages and process inputs and outputs are clearly defined which helps the managers to successfully develop the suppliers. Originality/value This paper puts forward the process model that should be implemented for the successful development of green suppliers. It might represent new opportunities for rigorous and relevant research in the area of green supply chain.

scholarly journals Evaluation and Segmentation of Printing Accessories Suppliers Based on the Integration of the Best Worst Method and Fuzzy TOPSIS (Case Study at PT. Udaka Indonesia)

OPSI ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 146
Author(s):  
Wakhid Nur Hidayat ◽  
Elly Wuryaningtyas Yunitasari ◽  
Patrisius Edi Prasetyo
Keyword(s):  
Product Development ◽  
Development Process ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Raw Material ◽  
Product Development Process ◽  
Supplier Evaluation ◽  
Industrial Environment ◽  
Best Worst Method

In an increasingly competitive industrial environment, every company strives to increase the quality and efficiency of its product development process. PT. Udaka Indonesia, a clothing manufacturer, is experiencing raw material shortages that disrupt the company's production process. The goal of this research is to assess and segment the company's suppliers. The Best Worst Method (BWM) is employed for weighting criteria, and Fuzzy TOPSIS is used to rank alternative providers and subsequently segment them. The dimensions of capabilities (8 criteria with 26 sub-criteria) and willingness (4 criteria with 15 sub-criteria) make up the company's supplier evaluation criteria. The evaluation results suggest that suppliers A2, B2, C2, and D2 are the best in terms of capabilities for label accessories, stickers, paper tags, and polybags, respectively, while A1, B2, C2, and D2 are the best in terms of willingness. Supplier segmentation results show that segmentation 1 includes suppliers C1, B1, B3, and D1, segmentation 2 includes supplier A3, and segmentation 4 includes suppliers A1, A2, B2, B4, C2, and D2. 

scholarly journals Identification of critical factors for the implementation of reverse logistics in the manufacturing industry of Pakistan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yousaf Ali ◽  
Khaqan Zeb ◽  
Abdul Haseeb Khan Babar ◽  
Muhammad Asees Awan
Keyword(s):  
Best Practices ◽  
Reverse Logistics ◽  
Design Methodology ◽  
Manufacturing Industry ◽  
Manufacturing Sector ◽  
Fuzzy Topsis ◽  
Content Type ◽  
Fuzzy Vikor ◽  
Major Facilitator ◽  
Practical Implications

Purpose The purpose of this research is to identify major barriers to the implementation of reverse logistics (RL). Also, the study addresses best practices among reuse, remanufacture, recycling, refurbishment and repair as alternatives for RL processes. Design/methodology/approach This study targets supply chain management experts for their opinions regarding the identification of critical barriers and alternatives for RL implementation. Their opinions were extracted through a Web questionnaire based on 14 criteria with 5 alternatives. The tools of multi-criteria decision-making are used for analysis, i.e. fuzzy VIKOR and fuzzy TOPSIS. Findings The results indicate that lack of recognition of competitive advantage to be gained through RL practice is the most critical barrier to RL implementation. The least barrier or major facilitator for RL is “supportive initiative for end-of-life products.” The top-ranked alternative in this study is reuse followed by remanufacturing. The least important alternative is “repair” in the case of Pakistan. These alternatives are ranked based on “q values” derived through fuzzy VIKOR. Research limitations/implications The results of this study can only be generalized for the manufacturing sector of Pakistan during the period of the study. Practical implications The findings of this study will assist managers in deploying the best practices concerning RL. Originality/value Fuzzy VIKOR and fuzzy TOPSIS have not been applied to RL alternatives in previous research.

An Integrated QFD-TOPSIS Approach for Supplier Selection Under Fuzzy Environment

2018 ◽  
Vol 9 (3) ◽  
pp. 62-81 ◽  
Author(s):  
Bentolhoda Rahpeyma ◽  
Mahnaz Zarei
Keyword(s):  
Supplier Selection ◽  
Quality Function Deployment ◽  
Manufacturing Industry ◽  
Integrated Approach ◽  
Service Industries ◽  
Multi Index ◽  
Fuzzy Environment ◽  
Topsis Approach ◽  
Index Problem

This article describes how supplier selection is a multi-index problem which affects the efficiency of the whole supply chain in both manufacturing and service industries. Considering the importance of selecting effective suppliers, this article aims to integrate two well-known techniques, Quality Function Deployment (QFD) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in order to evaluate suppliers and rank them based on their merits. In order to handle the inherent uncertainty in the process of experts' judgments, fuzzy logic is involved in the methodology applied in this study. The validity of the utilized integrated approach is demonstrated through conducting a case study in the detergent manufacturing industry in Iran.

scholarly journals SIMILARITY BASED FUZZY INFERIOR RATIO FOR SOLVING MULTICRITERIA DECISION MAKING PROBLEMS

2020 ◽  
Vol 5 (2) ◽  
pp. 597
Author(s):  
Sharifah Aniza Sayed Ahmad ◽  
Daud Mohamad ◽  
Nurul Iffah Azman
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Compromise Solution ◽  
Fuzzy Environment ◽  
Order Preference ◽  
Topsis Technique ◽  
Distance Approach

The method of Fuzzy Inferior Ratio (FIR) has been recognized as one of advantageous methods in multi criteria decision-making under fuzzy environment as it considers the element of compromise solution between the positive and negative aspect of the evaluation simultaneously. It is considered as an improvised version of Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method for solving decision-making problems. However, the FIR utilizes the distance approach in the evaluation in obtaining the compromise solution. A defuzzification process is carried out to transform the fuzzy values into a crisp form. Hence, loss of information may occur in the computation. In this paper, we proposed a similarity-based FIR in order to overcome the above-mentioned problem. A new compromise solution for the proposed FIR is developed and an improvised procedure of FIR is suggested using the similarity measure approach. A comparative analysis between the distance based and the similarity-based FIR is carried out using a case study of preferred client selection for a loan application. The proposed method is found to be effective in solving decision-making problems as the utilization of similarity measure will sufficiently preserve the data information in the computational process of evaluation.  

scholarly journals Model for ore deposits selection by using the fuzzy TOPSIS method

2020 ◽  
Vol 56 (1) ◽  
pp. 59-71
Author(s):  
G. Popović ◽  
D. Stanujkić ◽  
D. Karabašević ◽  
Z. Štirbanović
Keyword(s):  
Decision Making ◽  
Evaluation Model ◽  
Evaluation Criteria ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Topsis ◽  
Ore Deposits ◽  
Decision Makers ◽  
Fuzzy Environment ◽  
Proposed Model ◽  
Ambiguous Data

Decision-makers are often being faced with imprecise and ambiguous data. In such circumstances, the use of extended Multiple-Criteria Decision-Making (MCDM) method is more appropriate than the use of other classic decision-making techniques. This paper develops an evaluation model based on the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to help the selection of the appropriate ore deposit for exploitation in a fuzzy environment. The applicability of the proposed model is demonstrated with a real case study involving four alternative ore deposits, seven evaluation criteria, and 3 decision-makers.

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