Adhami, AY and Melethil, A and Ahmad, F (2023) Neutrosophic programming approach to multilevel decision-making model for supplier selection problem in a fuzzy situation. In: RAIRO - Operations Research, 57 (3). pp. 1307-1328.
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Abstract
In supply chain management, the selection of suppliers is vital and plays a valuable role in the performance of organizations. A hierarchical structure, with different levels in the selection of suppliers, is employed, wherein sequential decisions are made from the highest to the lowest level. Decision variables, called controlling factors, are divided into several categories. In the decision-making process, often because of the lack of confidence or uncertainty, It becomes challenging for decision-makers to give explicit/crisp values to any parameter, resulting in uncertainty in the problem. In this paper, we address a multi-level supplier selection problem with fuzzy supply and demand. To avoid decision conflicts, superior or upper-level decision-makers give tolerances that could be used as a possible relaxation. Thus, the problem is employed with fuzzy constraints. Based on a neutrosophic decision set, the neutrosophic compromise programming approach (NCPA) is used as a solution technique with the idea of an indeterminacy degree as well as different objectives for membership and non-membership degrees. Membership functions (Linear-type) are used to develop satisfactory solutions by fuzzily describing objective functions and controlling factors. A numerical illustration is provided to demonstrate the validity and appropriateness of NCPA.
| Item Type: | Journal Article |
|---|---|
| Publication: | RAIRO - Operations Research |
| Publisher: | EDP Sciences |
| Additional Information: | The copyright for this article belongs to the Author. |
| Keywords: | Indeterminacy membership function; Multilevel programming; Neutrosophic compromise programming approach; Supplier selection; Supply chain. |
| Department/Centre: | Division of Interdisciplinary Sciences > Management Studies |
| Date Deposited: | 20 Jul 2023 08:51 |
| Last Modified: | 20 Jul 2023 08:51 |
| URI: | https://eprints.iisc.ac.in/id/eprint/82492 |
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