The Technique of Multi-criteria Decision-Making in the Study of Semi-structured Problems

  • Alexander N. PavlovEmail author
  • Dmitry A. Pavlov
  • Alexey A. Pavlov
  • Alexey A. Slin’ko
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 574)


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.


Criteria uncertainty Production model Reference situation of survey Theory of experiment planning Fuzzy measure 



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.


  1. 1.
    Mikoni, S.V.: Teorija prinjatija upravlencheskih reshenij. Uchebnoe posobie [Theory of administrative decision-making. Tutorial]. SPb.: Lan’. 448 p. (2015). (in Russian)Google Scholar
  2. 2.
    Mattila, V., Virtanen, K.: Ranking and selection for multiple performance measures using incomplete preference information. Eur. J. Oper. Res. 242(2), 568–579 (2015)Google Scholar
  3. 3.
    Korhonen, P.J., Silvennoinen, K., Wallenius, J., Öörni, A.: Can a linear value function explain choices? An experimental study. Eur. J. Oper. Res. 219(2). 360–367 (2012)Google Scholar
  4. 4.
    Petrovskij, A.B., Rojzenzon, G.V., Tihonov, I.P., Balyshev, A.V.: Retrospektivnyj analiz rezul’tativnosti nauchnyh proektov [A retrospective analysis of the performance of research projects]. Int. J. Inf. Models Anal. 1(4), 349–356 (2012). (in Russian)Google Scholar
  5. 5.
    Podinovski V.V.: Decision making under uncertainty with unknown utility function and rank-ordered probabilities. Eur. J. Oper. Res. 239(2), 537–541 (2014)Google Scholar
  6. 6.
    Larichev, O.I.: Verbal’nyj analiz reshenij [Verbal decision analysis]. M.: Nauka, 181 p. (2006). (in Russian)Google Scholar
  7. 7.
    Mikoni, S.V.: System analysis of multi-criteria optimization methods on a finite set of alternatives. In: Trudy SPIIRAN – SPIIRAS Proceedings, vol. 4, no. 41, pp. 180–199 (2015). (in Russian)Google Scholar
  8. 8.
    Mikoni, S.V.: Axioms of multicriteria optimization methods on a finite set of alternatives. In: Trudy SPIIRAN – SPIIRAS Proceedings, vol. 1, no. 44. pp. 198–214 (2016). (in Russian)Google Scholar
  9. 9.
    Sokolov, B.V., Moskvin, B.V., Pavlov, A.N., et al.: Voennaja sistemotehnika i sistemnyj analiz. Modeli i metody prinjatija reshenij v slozhnyh organizacionno–tehnicheskih kompleksah v uslovijah neopredeljonnosti i mnogokriterial’nosti: uchebnik [Military systems engineering and systems analysis. Models and methods of decision-making in complex technical–organizational systems in conditions of uncertainty and multicriteria]./Pod red. B.V. Sokolova. SPb.: VIKKU imeni A. F. Mozhajskogo, 496 p. (1999). (in Russian)Google Scholar
  10. 10.
    Nechetkie mnozhestva v modeljah upravlenija i iskusstvennogo intellekta [Fuzzy sets in management models and artificial intelligence]/Pod red. D.A. Pospelova. M.: Nauka, 312 p. (1986). (in Russian)Google Scholar
  11. 11.
    Pavlov, A.N., Sokolov, B.V.: Prinjatie reshenij v uslovijah nechetkoj informacii: ucheb. Posobie [Decision-making in conditions of fuzzy information: tutorial]. SPb.: GUAP, 72 p. (2006). (in Russian)Google Scholar
  12. 12.
    Zelentsov, V.A., Pavlov, A.N.: Multi-criteria analysis of the influence of individual elements on the performance of complex systems. Informacionno-upravljajushhie sistemy – Inf. Contr. Syst. 6(49), 7–12 (2010). (in Russian)Google Scholar
  13. 13.
    Pavlov, A., Sokolov, B., Pashchenko, A., Shalyto, A., Maklakov, G.: Models and methods for multicriteria situational flexible reassignment of control functions in man-machine systems. In: Proceedings of the 2016 IEEE 8th International Conference on Intelligent Systems, pp. 402–408 (2016)Google Scholar
  14. 14.
    Nogin, V.D.: Prinjatie reshenij v mnogokriterial’noj srede: kolichestvennyj podhod [Decision making in multicriteria environment: a quantitative approach]. M.: FIZMATLIT, 176 p. (2005). (in Russian)Google Scholar
  15. 15.
    Pyt’ev Ju, P.: Vozmozhnost’ kak al’ternativa verojatnosti. Matematicheskie i jempiricheskie osnovy, primenenie [The possibility alternatively probability. Mathematical and empirical basis, application]. M.: FIZMATLIT, 464 p. (2007). (in Russian)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Alexander N. Pavlov
    • 1
    • 2
    Email author
  • Dmitry A. Pavlov
    • 2
  • Alexey A. Pavlov
    • 2
  • Alexey A. Slin’ko
    • 2
  1. 1.Volga State University of TechnologyYoshkar-OlaRussia
  2. 2.Mozhaisky Military Space AcademySt. PetersburgRussia

Personalised recommendations