A new approach for ranking of trapezoidal fuzzy numbers

Abbasbandy, Saeid; Hajjari, Tayebeh

doi:10.1016/j.camwa.2008.10.090

Cited by 359 publications

(217 citation statements)

References 24 publications

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“…This concept was first proposed by Jain [7]. Some of the literatures that describe different approach of ranking fuzzy quantities are [1,3,4,10,[13][14][15]. Recently, ranking of trapezoidal fuzzy numbers based on the shadow length has been discussed by Pour et al [12].…”

Section: Introductionmentioning

confidence: 99%

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

2015

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Section: Introductionmentioning

confidence: 99%

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

2015

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“…It appears fundamental to utilise the final fuzzy scores of alternatives for profiling a final rank of the alternatives, in order to identify the best one, as this is an important component of the decision process. Abbasbandy and Hajjari (2009) reported more than 30 fuzzy ranking indices, although a heated debate has been developing about the counter-intuitiveness and absence of discrimination capability of many of these methods. According to Bortolan and Degani (1985), each ranking method involves some losing of information; still, nowadays, there is a lack of an universally accepted ranking methodology (Kaufmann and Gupta, 1988;Abbasbandy and Hajjari, 2009); Brunelli and Mezei (2013) have proven that rankings may differ significantly depending on the adopted methodology.…”

Section: An Integrated Model For Supplier Selectionmentioning

confidence: 99%

“…Abbasbandy and Hajjari (2009) reported more than 30 fuzzy ranking indices, although a heated debate has been developing about the counter-intuitiveness and absence of discrimination capability of many of these methods. According to Bortolan and Degani (1985), each ranking method involves some losing of information; still, nowadays, there is a lack of an universally accepted ranking methodology (Kaufmann and Gupta, 1988;Abbasbandy and Hajjari, 2009); Brunelli and Mezei (2013) have proven that rankings may differ significantly depending on the adopted methodology. Within ranking methods, defuzzification techniques provide a way to associate a crisp real number to fuzzy sets, in such a way that a ranking can be developed by utilizing a simple ordering relation.…”

Section: An Integrated Model For Supplier Selectionmentioning

confidence: 99%

Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment

Bruno

Esposito

Genovese

et al. 2016

Expert Systems with Applications

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Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) eprints@whiterose.ac.uk https://eprints.whiterose.ac.uk/ Reuse Unless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request.Applying supplier selection methodologies in a multi-stakeholder environment: a case study and a critical assessment In the contemporary global market, Supplier Selection represents a crucial process for enhancing firms' competitiveness. In firms operating in low-complexity sectors, Supplier Selection generally leverages on few significant variables (price, delivery time, quality) and it is often left to the buyers' experience. On the other hand, in industries characterised by remarkable product complexity, supplier selection systems gain the characteristics of a multistakeholder and multi-criteria problem, which needs to be theoretically formalized and realistically adapted to specific contexts. An increasing number of researches has been devoted to the development of different methodologies to cope with this problem. Nevertheless, while the number of applications is growing, there is little empirical evidence of the practical usefulness of such tools, that are mainly tested on numerical examples or computational experiments and focused on a dyadic version of the problem, overlooking the wider set of actors involved in the decision-making problem. The result is a clear dichotomy between academic theory and business practice. Therefore, the paper contributes to understand the above dichotomy by evaluating the applicability to real-world multi-stakeholder problems of the two main approaches proposed in the literature to deal with supplier selection, the Analytic Hierarchic Process (AHP) and the Fuzzy Set Theory (FST). Based on an industrial case study, a thorough discussion is developed, dealing with the issues arising during the implementation and practical functioning of such decision support systems, also providing provide practical guidelines and managerial implications.Keywords: supplier selection, analytic hierarchy process, fuzzy set theory, complex industries. Applying supplier selection methodologies in a multi-stakeholder environment:a case study and a critical assessment AbstractIn the contemporary global market, Suppli...

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“…Abbasbandy and Hajjari [1] proposed a new ranking method based on the left and the right spreads at some r -levels of fuzzy numbers by …”

Section: Ranking Of Triangular Fuzzy Numbersmentioning

confidence: 99%

“…Suppose x %is not a fuzzy Pareto-optimal solution for problem (1), then there exists a fuzzy Pareto-optimal solution x % . …”

Section: Proofmentioning

confidence: 99%

Fuzzy Pareto-optimal Solution to Fully fuzzy Multi Objective Linear Programming Problem

Mohanaselvi¹,

Ganesan²

2012

IJCA

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This paper proposes a new algorithm for the solution of fully fuzzy Multi objective linear programming problems involving triangular fuzzy number without converting them to equivalent classical problems. Based on the fuzzy ideal and fuzzy negative ideal solution of each single fuzzy objective function we propose an algorithm which provides a fuzzy Pareto-optimal solution for the given fully fuzzy multi objective linear programming problem. By the proposed method, the Decision Maker will have the flexibility of choosing [0,1]  r depending upon the situation and can obtain an improved fuzzy Pareto optimal solution. A numerical example is provided to illustrate the theory developed in this paper.

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A new approach for ranking of trapezoidal fuzzy numbers

Cited by 359 publications

References 24 publications

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment

Fuzzy Pareto-optimal Solution to Fully fuzzy Multi Objective Linear Programming Problem

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