Development of Score-based Ranking with an ’A posteriori’ Evaluation Feedback Methodology
Keywords:
score-based systems, generic simulator, genetic algorithmAbstract
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.
References
Csukás, B., Balogh, S. (1998). Combining Genetic Programming with Generic Simulation Models in Evolutionary Synthesis. Computers in Industry, 36(3), 181–197. https://doi.org/10.1016/S0166-3615(98)00071-2
Csukás, B., Balogh, S., Bánkuti, Gy. (2005). Generic Bi-layered Net Model – General Software for Simulation of Hybrid Processes, In: Daoliang Li and ÍBaoji Wang Eds.: Artificial Intelligence Applications and Innovations II. 2nd IFIP Conference of TC12 WG 12.5, Springer, 700–710.
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Copyright (c) 2006 Varga Mónika
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
