Семейство гибридных алгоритмов оптимизации и диагностирования…
9
[31]
Liu X.-X., Li J.-F., Hu X.-Y. Generalized inverse problems for part symmetric
matrices on a subspace in structural dynamic model updating.
Mathematical
and Computer Modelling
, 2011, vol. 53, no. 1–2, pp. 110–121.
[32] Christodoulou K., Ntotsios E., Papadimitriou C., Panetsos P. Structural model
updating and prediction variability using Pareto optimal models.
Computational
Methods in Applied Mechanics and Engineering
, 2008, vol. 198, no. 1,
pp. 138–149.
[33]
Zio E., Bazzo R. Multiobjective optimization of the inspection intervals of a
nuclear safety system: a clustering-based framework for reducing the Pareto
front.
Annals of Nuclear Energy
, 2010, vol. 37, no. 1, pp. 798–812.
[34]
Li X.Y., Law S.S. Adaptive Tikhonov regularization for damage detection
based on nonlinear model updating.
Mechanical Systems and Signal Pro-
cessing
, 2010,vol. 24, no. 2, pp. 1646–1664.
[35] Chu D., Lin L., Tan R.C.E., Wei Y. Condition numbers and perturbation analy-
sis for the Tikhonov regularization of discrete ill-posed problems.
Numerical
Linear Algebra with Applications
, 2011, vol. 18, no. 1, pp. 87–103.
[36] Kaltenbacher B., Kirchner A., Vexler B. Adaptive discretizations for the choice
of a Tikhonov regularization parameter in nonlinear inverse problems.
Inverse
Problems
, 2011, vol. 27, no. 12, pp. 1–28.
[37]
Сулимов В.Д., Шкапов П.М. Методология решения экстремальных задач для
механических и гидромеханических систем.
Вестник МГТУ им. Н.Э. Бау-
мана
.
Сер. Естественные науки
. Спец. вып. 2012, № 8, с. 17–34.
[38] Karmitsa N., Bagirov A., Mäkelä M.M. Comparing different nonsmooth mini-
mization methods and software.
Optimization Methods & Software
, 2012,
vol. 27, no. 1, pp. 131–153.
[39] Karmitsa N., Bagirov A. Limited memory discrete gradient bundle method for
nonsmooth derivative-free optimization.
Optimization
, 2012, vol. 61, no. 12,
pp. 1491–1509.
[40] Bagirov A.M., Jin L., Karmitsa N., Al Nuaimat A., Sultanova N. Subgradient
method for nonconvex nonsmooth optimization.
Journal of Optimization Theo-
ry and Applications
, 2013, vol. 157, no. 2, pp. 416–435.
[41] Astorino A., Frangioni A., Gaudioso M., Gorgone E. Piecewise quadratic ap-
proximations in convex numerical optimization.
SIAM Journal on Optimiza-
tion
, 2011, vol. 21, no. 4, pp. 1418–1438.
[42] Chen X. Smoothing methods for nonsmooth, nonconvex minimization.
Mathe-
matical Programming
.
Ser B
, 2012, vol. 134, no. 1, pp. 71–99.
[43] Bot R.I., Hendrich C. A double smoothing technique for solving unconstrained
nondifferentiable convex optimization problems.
Computational Optimization
and Applications
, 2013, vol. 54, no. 2, pp. 239–262.
[44] Сулимов В.Д. Локальная сглаживающая аппроксимация в гибридном ал-
горитме оптимизации гидромеханических систем.
Вестник МГТУ им.
Н.Э. Баумана. Сер. «Естественные науки»
, 2010, № 3, с. 3–14.
[45]
Floudas C.A., Gounaris C.E. A review of recent advances in global optimiza-
tion.
Journal of Global Optimization
, 2009, vol. 45, no. 1, pp. 3–38.
[46] Bertsimas D., Nohadami O. Robust optimization with simulated annealing.
Journal of Global Optimization
, 2010, vol. 48, no. 3, pp. 323–334.
[47]
Thangaraj R., Pant M., Abraham A., Bouvry P. Particle swarm optimization:
hybridization perspectives and experimental illustrations.
Applied Mathematics
and Computation
, 2011, vol. 217, no. 7(6), pp. 5208–5226.