A Hybrid Goal Programming, AHP, and ANP Approach for Multi-Criteria Decision-Making: Application to Supply Chain Management Optimization

Goal Programming (GP) is perhaps the most widely used multi-criteria decision-making (MCDM) technique that addresses complex decision problems involving multiple, conflicting objectives. However, GP has inherent limitations, particularly in handling subjective preferences and trade-offs decision criteria. This paper proposes a hybrid approach, combining Goal Programming (GP) with the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) to overcome these limitations. The integration of AHP and ANP with GP allows for better prioritization of decision criteria and trade-offs among them. The main contribution of this paper is to propose this unique AHP-ANP-GP methodology as a robust solution to multi-objective decision problems, enhancing decision-making accuracy and flexibility. Finally, the paper demonstrates the application of the proposed model to an important Supply Chain Management (SCM) problem: optimizing the trade-off between transportation and inventory costs.