Analytic Hierarchy Process (AHP) with MATLAB Implementation

As indicated by the title, the Analytic Hierarchy Process (AHP) is a decision analysis method commonly used to analyze and resolve complex decision-making problems. Although this method involves intricate calculations, numerous computational tools are now available, including MATLAB programs. Implementing AHP through MATLAB significantly enhances analysis efficiency and makes the method more accessible to users who are not well-versed in MATLAB programming. The MATLAB implementation typically involves several key steps: constructing pairwise comparison matrices using Saaty's scale (1-9), calculating priority weights through eigenvalue decomposition or approximation methods, and performing consistency checks using the Consistency Ratio (CR) calculation. Key functions often include matrix normalization, eigenvalue computation, and consistency validation algorithms. For practical implementation, the MATLAB code generally follows this structure: 1. Input layer: Defining the hierarchy structure and comparison matrices 2. Processing layer: Calculating weight vectors using eigenvector methods 3. Validation layer: Checking consistency with threshold values (CR < 0.1) 4. Output layer: Generating priority rankings and sensitivity analysis Therefore, if you intend to solve decision-making problems using AHP, I recommend learning how to utilize MATLAB programs for analysis, as they provide automated calculation workflows and reduce manual computation errors while maintaining methodological rigor.