A Literature Review on Supplier Selection Problem and Fuzzy Logic

Paldrak, Mert; Erdem, Gamze; Taçoğlu, Melis; Güçlükol, Simge; Staiou, Efthymia

doi:10.1007/978-3-031-09173-5_42

Cited by 3 publications

(1 citation statement)

References 44 publications

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“…Supplier selection is a complex decision-making problem, comprising several suppliers as the candidates and a set of criteria that often have conflicts. To solve this problem and achieve optimized solutions, various multi-criteria decision-making (MCDM) methods are vastly employed (Paldrak et al, 2022;Resende et al, 2021;Schramm et al, 2020;Chai & Ngai, 2020;Konys, 2019;Aouadni et al, 2019;Wetzstein et al, 2016). Strong supplier management maximizes cost-reduction opportunities, value-driven services, and overall systemic efficiencies of the organizations.…”

Section: Introductionmentioning

confidence: 99%

Introducing Alternatives Ranking With Elected Nominee (Arwen) Method: A Case Study of Supplier Selection

Zakeri,

Chatterjee,

Konstantas

et al. 2023

Technological and Economic Development of Economy

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Supply chain management (SCM) has gradually evolved beyond the straightforward logic of benefits and economic viewpoints. Supplier selection and performance evaluation are the crucial strategic components of any SCM system with a substantial economic impact and risk reduction. Several conflicting factors make supplier selection a challenging multi-criteria decision-making problem. This paper introduces a method called alternative ranking with the elected nominee (ARWEN) to select suppliers in Iran’s dairy product chain store. The primary principle of ARWEN is to choose the best alternative based on the lowest change rate rather than the elected nominee. Four extensions of the ARWEN method are proposed depending upon the nature and level of information available to the decision-makers. A fifth extended version termed E-ARWEN is also recommended to consider the negative form of the elected nominee. Two novel statistical tools, the ranking performance index and the Zakeri-Konstantas distance product correlation coefficient, are also put forth to validate the ARWEN extensions’ outcomes. The results and verification of this new method are carried out through two supplier selection case examples. Comprehensive comparisons were carried out to explore the new methods’ behaviors, indicating ARWEN III and E-ARWEN have similar behavior to VIKOR, SAW, and EDAS in generating rankings.

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