Nogin Vladimir Dmitrievich

Publications in Math-Net.Ru

1. Multicriteria choice based on interval fuzzy information
   
   Artificial Intelligence and Decision Making, 2023, no. 4,  82–93
2. Algorithm for reduction of the Pareto set using a collection of fuzzy information quanta
   
   Artificial Intelligence and Decision Making, 2022, no. 4,  3–12
3. Type-2 fuzzy sets and their application in decision-making. Implementation
   
   Artificial Intelligence and Decision Making, 2021, no. 2,  21–34
4. Type-2 fuzzy sets and their application in decision-making summary. General concepts
   
   Artificial Intelligence and Decision Making, 2021, no. 1,  3–14
5. The Edgeworth–Pareto principle in the case of a 2-type fuzzy preference relation summary
   
   Artificial Intelligence and Decision Making, 2020, no. 2,  51–62
6. Multicriteria choice based on fuzzy information
   
   Artificial Intelligence and Decision Making, 2019, no. 2,  50–61
7. Ultimate possibilities of the Рareto set reduction based on quanta of fuzzy information
   
   Artificial Intelligence and Decision Making, 2017, no. 4,  69–77
8. Pareto set reduction based on an axiomatic approach with application of some metrics
   
   Zh. Vychisl. Mat. Mat. Fiz., 57:4 (2017),  645–653
9. Composed approach to reduce the Pareto set using linear or multiplicative scalarization
   
   Artificial Intelligence and Decision Making, 2016, no. 2,  70–77
10. Generalized Edgeworth–Pareto principle
    
    Zh. Vychisl. Mat. Mat. Fiz., 55:12 (2015),  2015–2021
11. Weighted sum scalarization in multicriteria optimization
    
    Artificial Intelligence and Decision Making, 2014, no. 4,  73–82
12. An algorithm of Pareto set reducing based on arbitrary finite collection of “quanta” of information
    
    Artificial Intelligence and Decision Making, 2013, no. 1,  63–69
13. Reducing the Pareto set based on information about the DM’s set-point type preference relation
    
    Artificial Intelligence and Decision Making, 2010, no. 2,  54–63
14. Pareto set reducing based on information about the DM’ preference relation of point-set type
    
    Artificial Intelligence and Decision Making, 2009, no. 1,  5–16
15. Pareto set reducing problem: approaches to solution
    
    Artificial Intelligence and Decision Making, 2008, no. 1,  98–112
16. Using interdependent information on the relative importance of criteria in decision making
    
    Zh. Vychisl. Mat. Mat. Fiz., 46:12 (2006),  2178–2190
17. The Edgeworth–Pareto principle in terms of a fuzzy choice function
    
    Zh. Vychisl. Mat. Mat. Fiz., 46:4 (2006),  583–592
18. A simplified variant of the hierarchy analysis on the ground of nonlinear convolution of criteria
    
    Zh. Vychisl. Mat. Mat. Fiz., 44:7 (2004),  1261–1270
19. The Edgeworth-Pareto principle and relative importance of criteria in the case of a fuzzy preference relation
    
    Zh. Vychisl. Mat. Mat. Fiz., 43:11 (2003),  1666–1676
20. A logical justification of the Edgeworth–Pareto principle
    
    Zh. Vychisl. Mat. Mat. Fiz., 42:7 (2002),  951–957
21. Using quantiative information on the relative importance of criteria for decision making
    
    Zh. Vychisl. Mat. Mat. Fiz., 40:11 (2000),  1593–1601
22. Duality in multipurpose programming
    
    Zh. Vychisl. Mat. Mat. Fiz., 17:1 (1977),  254–258


23. Я. Крейчи. Матрицы парных сравнений и их нечеткое расширение. Новый нечеткий подход к принятию решений при многих критериях
    
    Artificial Intelligence and Decision Making, 2021, no. 1,  98–99
24. Multicriteria choice over the fuzzy set as a problem of compromise search
    
    Artificial Intelligence and Decision Making, 2018, no. 3,  91–99