Abstract
This study proposes a scientific and methodical approach to problem solving automation, and intellectualization of multi-criteria decision-making (DM) processes for complex objects management. The substantiation of the composition and structure of the Intelligent Distributed Decision Support System (IDDSS) in complex objects management is based on a methodology developed by the authors and technologies of proactive monitoring and management of the structural dynamics of systems. The essence of the proposed technology of criterion uncertainty resolution is the joint use of the ideas of verbal analysis of decisions (simple and complex reference situation of the survey) and procedures of bringing data qualitative indicators to quantitative ones based on using the mathematical apparatus of theory of fuzzy sets, relations and measures, and the theory of experiment planning.
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Acknowledgement
The research described in this paper is partially supported by the Russian Foundation for Basic Research (grants 16-29-09482-fi-i, 17-08-00797, 17-06-00108, 17-01-00139, 17-20-01214, 17-29-07073-fi-i, 18-07-01272, 18-08-01505, 19-08-00989) state order of the Ministry of Education and Science of the Russian Federation 2.3135.2017/4.6, state research 0073-2019-0004, International project ERASMUS +, Capacity building in higher education, 73751-EPP-1-2016-1-DE-EPPKA2-CBHE-JP, Innovative teaching and learning strategies in open modelling and simulation environment for student-centered engineering education.
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Pavlov, A.N., Pavlov, D.A., Zakharov, V.V. (2020). Technology Resolution Criterion of Uncertainty in Intelligent Distributed Decision Support Systems. In: Kotenko, I., Badica, C., Desnitsky, V., El Baz, D., Ivanovic, M. (eds) Intelligent Distributed Computing XIII. IDC 2019. Studies in Computational Intelligence, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-32258-8_43
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