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Портал Begell Электронная Бибилиотека e-Книги Журналы Справочники и Сборники статей Коллекции
Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Печать: 1064-2315
ISSN Онлайн: 2163-9337

Выпуски:
Том 52, 2020 Том 51, 2019 Том 50, 2018 Том 49, 2017 Том 48, 2016 Том 47, 2015 Том 46, 2014 Том 45, 2013 Том 44, 2012 Том 43, 2011 Том 42, 2010 Том 41, 2009 Том 40, 2008 Том 39, 2007 Том 38, 2006 Том 37, 2005 Том 36, 2004 Том 35, 2003 Том 34, 2002 Том 33, 2001 Том 32, 2000 Том 31, 1999 Том 30, 1998 Том 29, 1997 Том 28, 1996

Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v46.i2.30
pages 27-41

Stability and Effective Algorithms for Solving Multiobjective Discrete Optimization Problems with Incomplete Information

Vladimir A. Emelichev
Byelorussian State University, Minsk
Vladimir M. Kotov
Byelorussian State University, Minsk
Kirill G. Kuzmin
Byelorussian State University, Minsk
Tatyana T. Lebedeva
V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine, Kiev
Natalya V. Semenova
V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine, Kiev
Tatyana I. Sergienko
V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine, Kiev

Краткое описание

The stability problem of vector discrete optimization problems with different principles of optimality with respect to perturbations of all input data of the problem is investigated based on the obtained results on the stability kernel property and the subset of those feasible solutions which steadily do not belong to the optimum set. We present the review of the latest results concerning the estimations of stability radius of solutions of Boolean multicriteria problems with nonlinear criteria. For the problem with the known optimum value of the goal function there is constructed the algorithm with the best known guaranteed estimation. The described scheme applied group technologies and dynamic lower estimations for the optimum value of the objective functional which can be used in various versions of problems with incomplete information.


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