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First and Second Order Necessary Conditions of Optimality for Impulsive Control Problems
Arutyunov A., Dykhta V., Pereira F.
We present first and second order necessary conditions of optimality for a general class
Multidimensional central limit theorem for sums of functions of the trajectories of endomorphisms
Dubrovin V., Gabbasov F., Chebakova V.
almost optimal rate of convergence to the normal distribution. In the proof we use “method of successive
Sequential threshold control in descent splitting methods for decomposable optimization problems
Konnov I.
for decomposable composite optimization problems, which maintains the basic convergence properties, but enables one
One approach for solving optimization problems with apriori estimates of approximation of admissible set
Andrianova A.
solutions to a constrained optimization problem are studied. The replacement of the initial admissible set
МОДЕЛЬ ФОРМИРОВАНИЯ ПРОГРАММЫ РАЗВИТИЯ СИСТЕМЫ ОБЕСПЕЧЕНИЯ ИНФОРМАЦИОННОЙ БЕЗОПАСНОСТИ ОРГАНИЗАЦИИ
Зегжда П.Д., Зегжда Д.П., Анисимов В.Г., Анисимов Е.Г., Сауренко Т.Н.
of improving the methodological apparatus for substantiating appropriate decisions in planning and managing
A globally convergent Levenberg–Marquardt method for equality-constrained optimization
Izmailov A.F., Solodov M.V., Uskov E.I.
well when applied to the specific case of the Lagrange optimality system, i.e., to the equation given
An optimal and quasi-optimal alternatives determination in the multicriteria marketing researches
Shikhalev A., Vorontsov D., Khamidullina G., Solovev D.
to find the alternative which is optimal to the all used criteria. The intermediate stage is the ranging
Consensus of large-scale group decision making in social network: the minimum cost model based on robust optimization
Lu Y., Xu Y., Herrera-Viedma E., Han Y.
Recently, large-scale group decision making (LSGDM) in social network comes into being
Some new facts about sequential quadratic programming methods employing second derivatives
Izmailov A.F., Solodov M.V.
For the sequential quadratic programming method (SQP), we show that close to a solution satisfying
Enhancing heart disease prediction using gaussian process regression and sequential analysis for optimal sampling efficiency
He, Runhai, Li, Fusheng, Zhang, Zhenxing, Zhang, Shoujing
with sequential analysis, we found appropriate sampling stops to reduce acquisition costs while maintaining

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