Supplier Evaluation And Demand Forecasting For Optimizing Order Allocation

Abstract

This thesis offers a thorough model for supplier selection and order distribution for a sweet potato starch producing business that buys both purple and white sweet potatoes. The Analytic Hierarchy Process (AHP) is used in the study to determine the criteria weights for supplier evaluation, and the FTOPSIS approach is used to determine the supplier weights based on the decision makers' assessments and the produced criteria weights. After evaluating numerous forecasting techniques, the study chooses Seasonal Autoregressive Integrated Moving Average (SARIMA) for its accuracy in demand prediction. A multi-objective model that incorporates supplier weights and anticipated demand is solved using CPLEX optimization with the primary goals being total cost, on-time delivery, damage rate, and supplier score. The suggested model attempts to improve operations, create better supplier collaboration, and increase supply chain efficiency while offering useful insights for related businesses seeking sustainable growth.