Supplier selection and order allocation with quantity discount and demand uncertainty: A case study of ABC company

Abstract

Order planning is considered to be one of the most important process in determining the competitive advantage and performance of a company. Through selecting capable suppliers and allocating orders strategically from each of them, operating cost can be optimized significantly. In order to help ABC company achieve this goal, this thesis aims to propose a model integrating fuzzy TOPSIS to evaluate and rank the suppliers, then using that results as inputs into a bi objective linear programming to allocate the order quantity to each suppliers so that the total value purchased from high-priority supplier can be maximized and the total cost of ordering, purchasing, and imventory can be minimized in a multi-item, muli-period environment with deman uncertainty considered. Moreover, an all-unit quantity discount scheme will also be intergrated based on the realistic scenario of ABC company. The proposed model will be solved with CPLEX programming to suggest a comprehensive supplier selection and order allocation framework that is expected to improve the overall supply chain efficiency of the company.