Demand Forecasting And Supplier Evaluation For Sustainable Order Allocation With Multiple Products

Abstract

This study's major goal is to suggest an integrated method for choosing sustainable suppliers and allocating orders. This paper specifically tries to achieve three goals. First, an appropriate analysis is carried out to examine and pinpoint any gaps in earlier works on supplier selection and order allocation models. Second, a forecasting procedure based on machine learning algorithm is developed to forecast demand and an MCDM – Mathematical programming model, which takes into account four sustainable elements, is used to efficiently assign purchase orders to suppliers based on evaluation results. This model takes into account order distribution across different time periods with multiple products. The developed model is then tested for amount of sensitivity to parameter changes using a case study in a real-world supply chain environment.