Priority Derivation from Pairwise Comparison Matrices by Multi-Objective Evolutionary Computing

The paper investigates the application of evolutionary algorithms (EA) for solving prioritisation problems, in the framework of the Analytical Hierarchy Process. A new two-objective prioritization (TOP) method was proposed recently by the author, where the prioritisation problem is formulated as an optimization task for minimization of the Euclidean norm and the number of rank violations. The TOP method derives Pareto optimal solutions, which requires the application of efficient computational algorithms. We propose two evolutionary computing approaches, based on single-objective and multi-objective evolutionary algorithms. Our preliminary results from a Monte-Carlo simulation show that the multi-objective EA outperforms the single-objective solution approach with respect to accuracy and computational efficiency