Development of Score-based Ranking with an ’A posteriori’ Evaluation Feedback Methodology

Abstract

University of Kaposvár, Department of Information Technology, H-7400, Kaposvár, Guba S. 40. The efficiency of the score-based ranking systems has studied with one method of the artificial intelligence. 182 already realized tenders were studied with the help of the bi-layered net model based generic simulator, combined with the multiobjective genetic algorithm. The essence of the methodology is that considering the ’a posteriori’ opinion of the experts about the best and worst tenders, we try to develop a better set of the score limits, which would rank the tenders being best and worst accordingly. As another result we demonstrate the applicability of the artificial intelligence method for the solution of this class of problems.