Dataset Information

Green Supplier Selection Using Fuzzy Multiple-Criteria Decision-Making Methods and Artificial Neural Networks.

ABSTRACT: In recent years, environmental awareness has increased considerably, and in order to decrease endangerments such as air and water pollution, and also global warming, green procurement should be employed. Therefore, in the assessment of suppliers, their environmental performance should be taken into consideration along with other criteria for supplier selection. Raising awareness of sustainability in production and conservation and protection of the environment is very important both for the whole environment and for the company itself by increasing its competitive advantage. And, one of the steps to achieve this is for the companies to try to select green suppliers. So, the purpose of this study is to raise awareness and tackle the need for green supplier selection and, using multiple-criteria decision-making models, to elaborate a case study regarding this. A survey was conducted in a manufacturing firm. The data were analysed, and fuzzy MCDM (multicriteria decision-making) methods and artificial neural networks were implemented. Fuzzy methods are the fuzzy analytic hierarchy process (fuzzy AHP), fuzzy TOPSIS, and fuzzy ELECTRE. ANN supports the result of fuzzy MCDM models from the profit side. ANN can make the best estimate of the current year based on historical data. Fuzzy MCDM methods will also find good solutions using the available data but will produce different solutions as there are different decision-making methods. It is aimed to produce a synergy from the solutions obtained here and to produce a better solution. Instead of a single method, it would be more accurate to produce a better solution than the solution provided by all of them. The dominant result has been obtained using the committee fuzzy MCDM and ANN to select the best green supplier.

SUBMITTER: Gegovska T

PROVIDER: S-EPMC7566219 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Green Supplier Selection Using Fuzzy Multiple-Criteria Decision-Making Methods and Artificial Neural Networks.

Gegovska Tina T Koker Rasit R Cakar Tarik T

Computational intelligence and neuroscience 20200930

In recent years, environmental awareness has increased considerably, and in order to decrease endangerments such as air and water pollution, and also global warming, green procurement should be employed. Therefore, in the assessment of suppliers, their environmental performance should be taken into consideration along with other criteria for supplier selection. Raising awareness of sustainability in production and conservation and protection of the environment is very important both for the whol ...[more]

PMID: 33082775

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Project description:In supply chain literature, supplier evaluation and selection problem is one of the most studied subjects because of the significant roles of suppliers in terms of the chain's sustainability and profitability. Therefore, it is important for organizations to adopt a systematic way to evaluate and select the best supplier according to their respective criteria in today's competitive environment. Multicriteria decision-making methods provide for this need of organizations because determination of an appropriate supplier selection is a multicriteria decision-making (MCDM) problem essentially. Although a lot of applications of these methods for supplier evaluation and selection can be seen in the literature, studies in the health-care sector are insufficient. Hospitals in the health-care sector also have to consider their supplier-related decisions to decrease risks and threads which affect their effectiveness. The aim of this study was to fill this gap by providing different hybrid models for selecting the best supplier for hospitals. Supplier evaluation and selection process start with recognizing the related criteria according to the studies in the literature. Analytic hierarchy process (AHP) method is deployed to weight the criteria, and suppliers are listed via technique for order preference by similarity to ideal solution (TOPSIS), elimination and choice translating reality English (ELECTRE), grey relational analysis (GRA), and simple additive weighting (SAW) methods. The main aim of this study was to present different hybrid MCDM methods and show their efficiency and consistency with each other. In this study, hybrid multicriteria decision-making models (AHP-TOPSIS, AHP-ELECTRE, AHP-GRA, and AHP-SAW) are presented and compared. The results show that the presented hybrid methods in this study are consistent with each other and give the same ranking for the selection of the best supplier. It can be considered as a useful guideline for hospitals.

Dataset Information

Green Supplier Selection Using Fuzzy Multiple-Criteria Decision-Making Methods and Artificial Neural Networks.

Publications

Green Supplier Selection Using Fuzzy Multiple-Criteria Decision-Making Methods and Artificial Neural Networks.

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