| dc.description.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 biobjective 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 | en_US |
