Optimization of operational costs for a single supplier - manufacturer supply chain

This thesis considers a simple supply chain with one supplier and one manufacturer. The supplier provides batches of items to meet the manufacturer's demand targets. The manufacturer tries to choose the right order quantities of items to minimize total operational cost. The cost is made up of inventory and transportation costs which both are functions of order quantity. The inventory costs include holding costs, purchasing costs, ordering costs and financing costs. The transportation costs include the expenses of shipping the items from the supplier to the manufacturer that are calculated with the National Motor Freight Classification (NMFC) standard. The Genetic Algorithm (GA) function in Matlab is used as the solution procedure and the results are compared with the Equal Order Quantity model and the Just-In-Time (JIT) model. The last part of this thesis presents a sensitivity analysis to establish the robustness of the model.