Abstract
In the article it is proposed to use additional information from the decision maker (DM) for removing the criteria of uncertainty when making decisions in the framework of semi-structured problems, which is characterized by incomplete information, numerous qualitative and the quantitative selection criteria. This information is represented by the production models and processed by using the methods of the experiment planning theory and parametric fuzzy measures. The essence of the proposed methodology consists of sharing the ideas of verbal analysis of the decisions (simple and complex basic situation of a survey) and procedures of bringing data qualitative indicators to the quantitative ones, which is based on using the mathematical apparatus of the theory of fuzzy sets, relations and measures, and the theory of experiment planning. A parametric fuzzy measure has been constructed in order to reduce the number of calls to the DM in the process of the expert survey and the consistency control of his statements in the set of the production rules that represent basic situation of the survey. This parametric fuzzy measure allows computing the DM’s preferences on criteria for achieving the goal set for making the management decisions.
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Acknowledgements
The research described in this paper is partially supported by the Russian Foundation for Basic Research (grants 15-07-08391, 15-08-08459, 16-07-00779, 16-08-00510, 16-08-01277,16-29-09482-ofi-i), grant 074-U01 (ITMO University), project 6.1.1 (Peter the Great St. Petersburg Polytechnic University) supported by Government of Russian Federation, Program STC of Union State “Monitoring-SG” (project 1.4.1-1), state order of the Ministry of Education and Science of Russian Federation № 2. 3135. 2017, State research 0073–2014–0009, 0073–2015–0007.
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Pavlov, A.N., Pavlov, D.A., Pavlov, A.A., Slin’ko, A.A. (2017). The Technique of Multi-criteria Decision-Making in the Study of Semi-structured Problems. In: Silhavy, R., Senkerik, R., Kominkova Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Cybernetics and Mathematics Applications in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 574. Springer, Cham. https://doi.org/10.1007/978-3-319-57264-2_13
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