scholarly journals Fuzzy Similarity in Multicriteria Decision-Making Problem Applied to Supplier Evaluation and Selection in Supply Chain Management

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Pasi Luukka
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supplier Selection ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Topsis ◽  
Similarity Criteria ◽  
Fuzzy Decision Making ◽  
Ideal Solution ◽  
Supply Chain System ◽  
Fuzzy Similarity

It is proposed to use fuzzy similarity in fuzzy decision-making approach to deal with the supplier selection problem in supply chain system. According to the concept of fuzzy TOPSIS earlier methods use closeness coefficient which is defined to determine the ranking order of all suppliers by calculating the distances to both fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) simultaneously. In this paper we propose a new method by doing the ranking using similarity. New proposed method can do ranking with less computations than original fuzzy TOPSIS. We also propose three different cases for selection of FPIS and FNIS and compare closeness coefficient criteria and fuzzy similarity criteria. Numerical example is used to demonstrate the process. Results show that the proposed model is well suited for multiple criteria decision-making for supplier selection. In this paper we also show that the evaluation of the supplier using traditional fuzzy TOPSIS depends highly on FPIS and FNIS, and one needs to select suitable fuzzy ideal solution to get reasonable evaluation.

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 Multi-Criteria Decision-Making Model Based on Prospect Theory for Green Supplier Selection under Uncertain Environment: A Case Study of the Thailand Palm Oil Products Industry

2019 ◽  
Vol 11 (7) ◽  
pp. 1872 ◽  
Author(s):  
Patchara Phochanikorn ◽  
Chunqiao Tan
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Prospect Theory ◽  
Palm Oil ◽  
Supplier Selection ◽  
Large Scale ◽  
Oil Products ◽  
Green Supply Chain ◽  
Fuzzy Decision Making ◽  
Green Supplier Selection

Environmental concerns have globally driven the encouragement of green supply chain management. Accordingly, business and industrial organizations try to seek green supply chain strategies to respond to market pressure regarding corporate social responsibility. Green supplier selection is one of the practical strategies for modern enterprises. With the large-scale development of the palm oil products industry, green supplier selection technique is the key for decision making when dealing with mass information and possible risks of biased data. For instance, the preference of decision makers possibly causes a misleading decision, thus leading to unnecessary waste of resources. Therefore, the contribution of this paper is to apply the integrated multi-criteria decision method using the ‘fuzzy decision-making trial and evaluation laboratory’ (fuzzy DEMATEL) method to consider the cause and effect relationship and then using fuzzy analytic network process (fuzzy ANP) to assign the weight of each relevant criteria. The initial results are useful for strategic procurement planning. In the final step, we adopt the prospect theory to synthesize procurement’s psychological and behavioral factors when selecting green suppliers. The final result refers to the comprehensive prospect value to rank the eligible suppliers into orders. Moreover, the results of both sensitivity analysis and comparison method confirm that the proposed model is adequately realistic and robust.

Multiple-criteria fuzzy group decision-making with multi-choice goal programming for supplier selection: A case study

2019 ◽  
Vol 11 (03) ◽  
pp. 1950029
Author(s):  
Ashoke Kumar Bera ◽  
Dipak Kumar Jana ◽  
Debamalya Banerjee ◽  
Titas Nandy
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Supplier Selection ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Topsis ◽  
Multiple Criteria ◽  
Linguistic Variables ◽  
Manufacturing Organization ◽  
Fuzzy Group Decision Making

In today’s highly turbulent and competitive environment, the success of the organization depends on the performance of its suppliers. However, supplier selection problems are complex as they involve a large number of criteria and, frequently, some of the criteria cannot be evaluated precisely. Moreover, fluctuations of supplier performances and unknown information always exist in real-world decision-making. It is a complex multiple-criteria decision-making (MCDM) problem as it involves a trade-off among various criteria with vagueness and imprecision and also involves a group of experts with diverse opinion. Therefore, to make more practical decisions, this paper is intended to propose an integrated technique for order preference by similarity to ideal solution (TOPSIS) in fuzzy environment with multi-choice goal programming (MCGP) to handle the supplier assessment and order allocation for a battery manufacturing organization. Using linguistic variables, the decision-makers assess the rating of suppliers as well as the importance of various factors. Linguistic variables are expressed in trapezoidal fuzzy numbers (TrFN). Fuzzy-TOPSIS method is proposed to obtain the rank of suppliers and MCGP method is used to allocate suitable orders to the selected suppliers. A case study is implemented to find the applicability and validity of the proposed model. Finally, sensitivity analysis is performed to observe the effect of weights of criteria on supplier evaluation problem.

scholarly journals Supplier Selection Application Based on a Fuzzy Multiple Criteria Decision Making Methodology

2012 ◽  
Vol 3 (8) ◽  
pp. 7-18
Author(s):  
Hüseyin Selçuk KILIÇ
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supplier Selection ◽  
Selection Process ◽  
Multiple Criteria Decision Making ◽  
Working Environment ◽  
Multi Criteria Decision Making ◽  
Chain Management ◽  
Fuzzy Environment ◽  
Selection Methodology

Due to the increasing competitiveness in every sector of business life, being effective in every process of the organizations has been required. At this point, one of the most important processes is supplier selection process within the concept of supply chain management. If a systematic supplier selection methodology is performed, it will be possible to select the most suitable supplier and provide efficiency with respect to time, quality and cost. With this study, depending on the vague structure of the real working environment, an extensively used multi criteria decision making methodology TOPSIS is used within fuzzy environment. The proposed technique is applied in a real case and the most suitable suppliers are determined and ranked.

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.

scholarly journals A Fuzzy Multi Criteria Decision Making Approach for Vendor Evaluation in a Supply Chain

2010 ◽  
pp. 66-72
Author(s):  
Shalini Gupta ◽  
Alok Gupta
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Service Providers ◽  
Selection Process ◽  
Fuzzy Theory ◽  
Business Environment ◽  
Fuzzy Decision Making ◽  
Vendor Selection ◽  
Supply Chain System ◽  
Vendor Rating

Manufacturing enterprises face enormous competitive pressures in today’s business environment and to make full use of inside and outside resources in a competitive globalization market, many manufacturers and service providers are seeking a strategic cooperation with suitable vendors to improve their supply chain management (SCM) so that they can concentrate their efforts on their own core business. Hence, there is a necessary to select the best suppliers among various suppliers available. The decision parameters in vendor selection contains vague and uncertainty. The fuzzy theory able to handle this uncertainty, vague, imprecision and subjectivity present in vendor selection process and makes decision process more effective. In the research, we have analyzed an existing system of vendor rating and proposed a better system of vendor rating for the organization. Most organizations use simple additive weighting for vendor rating. However, we have attempted to use the fuzzy decision making method for the purpose. In the proposed approach, linguistic values are used to assess the ratings and weights for these factors. These linguistic ratings can be expressed in trapezoidal or triangular fuzzy numbers. Then, a hierarchy multiple criteria decision-making (MCDM) model based on fuzzy theory is proposed to deal with the supplier selection problems in the supply chain system.

scholarly journals Prioritization in Strategic Environmental Assessment Using Fuzzy TOPSIS Method with Random Generation for Absent Information in South Korea

2021 ◽  
Vol 13 (3) ◽  
pp. 1458
Author(s):  
Daeryong Park ◽  
Huan-Jung Fan ◽  
Jun-Jie Zhu ◽  
Taesoon Kim ◽  
Myoung-Jin Um ◽  
...  
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
River Basins ◽  
Ideal Solution ◽  
Missing Information ◽  
Nakdong River ◽  
Han River ◽  
Priority Ranking ◽  
The Nakdong River

This study evaluated a fuzzy technique for order performance by similarity to ideal solution (TOPSIS) as a multicriteria decision making system that compensates for missing information with undefined weight factor criteria. The suggested Fuzzy TOPSIS was applied to ten potential dam sites in three river basins (the Han River, the Geum River, and the Nakdong River basins) in South Korea. To assess potential dam sites, the strategic environment assessment (SEA) monitored four categories: national preservation, endangered species, water quality, and toxic environment. To consider missing information, this study applied the Monte Carlo Simulation method with uniform and normal distributions. The results show that effects of missing information generation with one fuzzy set in GB1 site of the Geum River basin are not great in fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) estimations. However, the combination of two fuzzy sets considering missing information in Gohyun stream (NG) and Hoenggye stream (NH) sites of the Nakdong River basin has a great effect on estimating FPIS, FNIS, and priority ranking in Fuzzy TOPSIS applications. The sites with the highest priority ranking in the Han River, Geum River, and Nakdong River basins based on Fuzzy TOPSIS are the Dal stream 1 (HD1), Bocheong stream 2 (GB2) and NG sites. Among the sites in all river basins, the GB2 site had the highest priority ranking. Consequently, the results coincided with findings of previous studies based on multicriteria decision making with missing information and show the applicability of Fuzzy TOPSIS when evaluating priority rankings in cases with missing information.

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