Abstract
The paper introduces Multiple Criteria Decision Making Problems with Incomplete Information (MCDMII). Usually such problems arise in Intelligent Decision Support Systems (IDSS) development or other cases of decision making practical realization. In most of cases, any practical problem is multicriteria, because a compromise between estimations by different criteria is necessary for the best solution choice [1]. On the other hand, it is a problem with incomplete information, because, as a rule, an exact setting of all data components in the decision making model is impossible [2].
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References
Larichev, O.: Objective models and subjective solutions. Nauka, Moscow. 1987.
Donskoy, V., Bashta, A.: Discrete models for decision making with incomplete information. Tavria, Simferopol. 1992
Donskoy, V., Perekhod, A.: On the multicriteria optimization problem with incomplete information about criteria. Abstracts of the International Conference in Multi-Objective Programming, Malaga, Spain, May 16–18, 1996, pp. 52–53
Perekhod, A.: Multicriteria decision making models with incomplete information for intelligent systems. Abstracts of the International Conference on Intelligent Data Processing, Alushta, Ukraine, June 3–7, 1996, pp. 27–28
Zakrevski, A.: Logic of the recognition. Nauka, Minsk. 1988
Donskoy, V.I.: Decision trees learning algorithms. Zh. Vychisl. Math. Math. Fiz. 22, 4 (1982) 963–974
Donskoy, V.I.: Weakly defined problems of Boolean linear programming with a partially specified set of admissible solutions. Zh. Vychisl. Math. Math. Fiz. 28, 9 (1988) 1379–1385
Tou, J., Gonzalez, R.: Pattern recognition principles. Addison-Wesley Publishing Company Inc., Advanced Book Program Reading, Massachusetts, London, etc. 1974
Orlov, V.: Graph-schemes of recognition algorithms. Nauka, Moscow. 1982
Perekhod, A.: The algorithm for Pareto sets approximation on multigraphs. Programs, Systems, Models. (1996) 18–26
Gamkrelidze, L. Ch., Ostroukh, E.N.: Methods for a solving of the discrete multicriteria optimization problems. Izv. Ross. Acad. Nauk, Tech. Cybem. 3 (1989) 150–155
Langley, P., Simon, H.: Application of Machine Learning and Rule Induction. Communications of the ACM. 38,11 (1995) 55–64
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© 1998 Springer-Verlag Berlin Heidelberg
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Perekhod, A. (1998). The Approach to Multicriteria Decision Making Based on Pattern Recognition Algorithms. In: Stewart, T.J., van den Honert, R.C. (eds) Trends in Multicriteria Decision Making. Lecture Notes in Economics and Mathematical Systems, vol 465. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45772-2_6
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DOI: https://doi.org/10.1007/978-3-642-45772-2_6
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