Multi-Criteria Multi-Period Supplier Selection and Order Allocation Models

Open Access
Ding, Ziqi
Graduate Program:
Industrial Engineering
Master of Science
Document Type:
Master Thesis
Date of Defense:
Committee Members:
  • Arunachalam Ravindran, Thesis Advisor
  • multiple criteria optimization
  • supply chain modeling
  • supplier selection
This thesis considers the use of multi-criteria optimization methods applied to supplier selection and order allocation problem over a planning horizon under multiple sourcing strategy. The supply chain system is modeled with a single buyer and multiple suppliers with deterministic demands as a mixed integer programming problem. We study the supplier selection and order allocation problem with three objectives. The criteria considered are (1) total cost over the planning horizon; (2) weighted average lead time and (3) weighted average quality defect rate. We first develop the mathematical formulation for all three objectives and then present a general multi-period and multi-criteria optimization model for the procurement problem. Two methods are used to solve the multi-criteria mathematical programming problem. The first approach is the Weighted Objective method. It is used to generate several efficient solutions by changing the weights assigned to the three criteria. The second approach is the Goal Programming method, which is used to generate the optimal solutions that can satisfy the specified targets set for the three criteria according to the decision maker’s preference. Several efficient points are generated by both Preemptive and Non-Preemptive Goal Programming methods. A numerical example is presented to illustrate both approaches. There are fourteen efficient solutions generated from both approaches. We compare the efficient solutions visually using the Value Path Approach. A sensitivity analysis is done to study the impact of changing the weight of the non-value added cost in the total cost objective.