In the ever‐changing world, vendor selection and evaluation are very important in supply chain management. Recently, there has been extensive research in the areas of vendor selection and evaluation under certainty/uncertainty without time axis, but there has been very little research in the selection of vendor with time axis. The purpose of this paper is to address this gap in the research.
Traditional approaches have been neglecting multi‐period planning horizon for vendor selection, and many decision makers or experts select vendors based on their practice and intuition. To overcome these problems, a dynamic model supporting vendors with time axis has been developed which is not always crisp, rather it involves a high degree of fuzziness and uncertainty. The authors use fuzzy analytic hierarchy process (AHP) to propose the decision model.
The research provides a mathematical system that captures the uncertainties associated with human cognitive processes in order to select the vendor. The findings of this study provide meaningful and advanced knowledge to decision makers by demonstrating a simple, efficient method to enhance the ability to predict an appropriate vendor period wise.
This research provides detailed step‐by‐step procedures to choose the best vendor selection and evaluation under uncertainty with time axis in a supply chain. It will be of value to other researchers and the department members in any firm who are responsible for selecting the vendor.
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