11 / 12
Адаптивные функции пригодности в эволюционных игровых моделях оптимизации управления…
ISSN 0236-3933. Вестник МГТУ им. Н.Э. Баумана. Сер. Приборостроение. 2017. № 2
121
[4] Harsanyi J.C. A general theory of equilibrium selection in games. MIT Press, 1988. 365 p. (Russ.
ed.: Obshchaya teoriya vybora ravnovesiya v igrakh. Sankt-Petersburg, Ekonomicheskaya shkola
Publ., 2001. 424 p.).
[5] Gusev M.I., Kurzhanskiy A.B. On equilibrium situations in multi-criteria game problems.
Dokl. AN SSSR,
1976, vol. 229, no. 6, pp. 1295–1298 (in Russ.).
[6] Moiseev N.N. Matematicheskie metody sistemnogo analiza [Mathematical methods of system
analysis]. Moscow, Nauka Publ., 1981. 487 p.
[7] Hervé Moulin. Théorie des jeux pour l'économie et la politique. Hermann, Paris, Collection
methodes, 1981. (Russ. ed.: Teoriya igr s primerami iz matematicheskoy ekonomiki. Moscow,
Mir Publ., 1985. 200 p.).
[8] Karpenko A.P. Sovremennye algoritmy poiskovoy optimizatsii. Algoritmy, vdokhnovlennye
prirodoy [Modern search optimization algorithms. Algorithms, inspired by nature]. Moscow,
Bauman MSTU Publ., 2014. 446 p.
[9] Rutkovskaya D., Pilin'skiy M., Rutkovskiy L. Neyronnye seti, geneticheskie algoritmy i
nechetkie sistemy [Neural networks, genetic algorithms and fuzzy systems]. Moscow, Goryachaya
liniya–Telekom Publ., 2006. 452 p.
[10]
Kureychik V.V., Kureychik V.M., Rodzin S.I. Teoriya evolyutsionnykh vychisleniy [Evolu-
tionary computations theory]. Moscow, Fizmatlit Publ., 2012. 260 p.
[11]
Ashlock D. Evolutionary computation for modeling and optimization. Berlin, Germany,
Springer-Verlag, 2006. 571 p.
[12]
Kita E., ed. Evolutionary algorithms. InTech, 2011. 596 p.
[13]
Dos Santos W.P., ed. Evolutionary computation. InTech, 2009. 582 p.
[14]
Zitzler E., Deb K., Thiele L. Comparison of multiobjective evolutionary algorithms: empirical
results.
Evolutionary Computation
, 2000, vol. 8, no. 2, pp. 173–195. DOI: 10.1162/106365600568202
Available at:
http://dl.acm.org/citation.cfm?id=1108876[15]
Serov V.A., Babintsev Yu.N., Kondakov N.S. Neyroupravlenie mnogokriterial'nymi kon-
fliktnymi sistemami [Neurocontrol on multicriteria conflict systems]. Moscow, MosGU Publ.,
2011. 136 p.
[16]
Serov V.A., Babintsev Yu.N., Chechurin A.V. Programmnoe sredstvo obucheniya iskusstven-
nykh neyronnykh setey na osnove kompleksa geneticheskikh algoritmov mnogokriterial'noy opti-
mizatsii v usloviyakh konflikta i neopredelennosti (MONS) [Software educational tool for artificial
neural networks based on complex of multicriteria optimization genetic algorithms under condi-
tions of conflict and uncertainty (MONS)]. Svidetel'stvo o gosudarstvennoy registratsii programmy
dlya EVM № 2011618436 ot 26.10.2011 g. [Computer program certificate of registration
№ 2011618436 dated 26.10.2011] (in Russ.).
[17]
Serov V.A., Khitrin V.V. Neurogenetic technology of multicriteria stabilization of technologi-
cal process operating mode under uncertainty conditions.
Promyshlennye ASU i kontrollery,
2011,
no. 6, pp. 38–42 (in Russ.).
[18]
Serov V.A., Khitrin V.V. Hybrid evolutionary algorithm for multicriteria optimization of bio-
technological process software mode.
Promyshlennye ASU i kontrollery
, 2010, no. 8, pp. 13–16 (in
Russ.).
[19]
Serov V.A., Babintsev Yu.N., Chechurin A.V. Neurogenetic technology of technological pro-
cess multi-criteria stabilization under uncertainty.
Neyrokomp'yutery: razrabotka i primenenie
[Industrial Automatic Control Systems and Controllers], 2008, no. 9, pp. 65–71 (in Russ.).
[20]
Serov V.A. Genetic algorithms of optimizing control of multiobjective systems under condi-
tion of uncertainty based on conflict equilibrium.
Vestn. Mosk. Gos. Tekh. Univ. im. N.E. Baumana,
Priborostr.
[Herald of the Bauman Moscow State Tech. Univ., Instrum. Eng.], 2007, no. 4,
pp. 70–80.