Pairwise Comparison of Mono-Interval Alternatives with Arbitrary Risk Distributions
- Authors: Shepelev G.I.1
-
Affiliations:
- Computer Science and Control Federal Research Center of the Russian Academy of Sciences
- Issue: No 4 (2022)
- Pages: 36-43
- Section: Optimal and Rational Choice
- URL: https://journal-vniispk.ru/2071-8594/article/view/270486
- DOI: https://doi.org/10.14357/20718594220404
- ID: 270486
Cite item
Full Text
Abstract
A method for comparing mono-interval alternatives is proposed, which makes it possible to compare in pairs the efficiency of alternatives with arbitrary risk distributions on interval estimates of their quality indicators. The application of the method is demonstrated by examples. Recommendations on the practical use of the method are given.
About the authors
Gennady I. Shepelev
Computer Science and Control Federal Research Center of the Russian Academy of Sciences
Author for correspondence.
Email: gis@isa.ru
Candidate of Physical and Mathematical Sciences, Senior Researcher, Leading Researcher
Russian Federation, MoscowReferences
- Vilensky P., Lifshits V., Smolyak S. “Otsenka effektivnosti investitsionnykh proyektov”. [“Evaluating effectiveness of investment projects”]. Moscow. PolyPrint Service. 2015.
- Zadeh, L.A. Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic //Fuzzy Sets and Systems 90.1997. P. 111–117.
- Shepelev G. Decision-making in groups of interval alternatives // International journal «Information theories and applications». 2016. 23(4). P. 303–320.
- Diligensky N., Dymova L., Sevastiyanov P. “Nechetkoe modelirovanie i mnogokriterialnaya optimizatsiya proizvodstvennykh system v usloviyakh neopredelennosti: tekhnologiya, ekonomika, ekologiya” [“Fuzzy modeling and multi-criteria optimization of production systems under uncertainty: technology, economy, ecology”]. Moscow: Engineering-1 Publs. 2004.
- Shepelev G. Comparing poly-interval alternatives: collective risk estimations method // Artificial intelligence and decision-making. 2019. No.3. P. 3-11.
- Nedosekin A. Nechetko-mnozhestvenny analiz riska finansovykh investitsy [Fuzzy-set analysis of financial investments risks]. SPb: Sesam. 2002.
- Fishburn P.C. Mean-risk analysis with risk associated with below-target returns // American Economic Review. 1977. 67(1). P. 116–126.
- Voshchinin A.P. Intervalny analiz dannykh: razvitie i perspektivy [Interval data analysis: development and prospective] // Zavodskaya laboratoriya [Diagnostics of materials]. 2002. V.68. No.1. P.118-126.
- Voshchinin A.P., Sotirov G.P. Optimizatsiya v usloviakh neopredelennosti [Optimization under uncertainty] MEI USSR, Tekhnika. PRB. 1989.
- Voshchinin A.P., Bochkov A.F., Sotirov G.P. Metod analiza dannykh pri intervalnoi nestatisticheskoi oshibke [A method for data analysis under interval nonstatistics error]// Zavodskaya laboratoriya [Diagnostics of materials]. 1990. V. 56. No. 7. P.76-81.
- Shakhnov I.F. Ekspress-analiz uporyadochennosti intervalnykh velichin [Express-analysis of interval values orderliness] // Avtomatika i telemekhanika [Automation and Remote Control]. 2004. No.10. P. 67–84.
- Shepelev G., Khairova N. Collective risk estimating method for comparing poly-interval objects in intelligent systems // COLINS-2021: 5th International Conference on Computational Linguistics and Intelligent Systems. CEUR Workshop Proceedings. 2021. Vol. 1-2870. P. 866-876.
- Zhiyanov V.I., Shepelev G.I. Kompleksny metod sravneniya alternativ v usloviyakh riska [Comprehensive method for comparing interval alternatives under risk] // Vestnik TSEMI [Herald of CEMI]. 3 [Electronic resource].
Supplementary files
