Integrating Hierarchical Clustering and Stochastic Multi-Objective Decision-Making for Optimized Decision Processes

Under uncertain business conditions, it might be challenging to manage the sustainable supplier selection challenge. This work is focused on applying a hybrid hierarchical cluster-stochastic optimization strategy to tackle the problem while considering robust and sustainable criteria. Initially, we recommend grouping high-dimensional supplier data using a hierarchical clustering algorithm. We created a stochastic goal programming model in the following phase to incorporate these factors into the decision-making procedure. The examination of the data reveals that the use of clustering algorithms improves supplier segmentation efficiency. The hybrid strategy that has been recommended is a helpful tool that reduces complexity, has the ability to be easily implemented, and elevates businesses' sustainable insights.