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Journal of Automation and Information Sciences

Publicado 12 números por año

ISSN Imprimir: 1064-2315

ISSN En Línea: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

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Some Approaches to Regularization of Nonlinear Optimization Problems

Volumen 43, Edición 5, 2011, pp. 40-51
DOI: 10.1615/JAutomatInfScien.v43.i5.40
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SINOPSIS

We consider ways of transformation of convex optimization problems with constraints to equivalent problems with better computational properties. Sufficient attention is paid to use of conic approximations and conic prolongation of objective functions from admissible domain of optimization problem on the whole space of variables. The problem of convex programming without constraints (regularized problem), which solution coincides with solution of the initial problem, is the result of usage of the suggested approach. The considered approaches have special significance when the objective function is not defined outside the admissible domain. We suggested efficient procedures for calculation of auxiliary functions, consider peculiarities of software support of algorithms, results of computational experiments.

CITADO POR
  1. Laptin Yu. P., Exact Penalty Functions and Convex Extensions of Functions in Schemes of Decomposition in Variables*, Cybernetics and Systems Analysis, 52, 1, 2016. Crossref

  2. Laptin Yu. P., Berezovskyi O. A., Using Conical Regularization in Calculating Lagrangian Estimates in Quadratic Optimization Problems, Cybernetics and Systems Analysis, 53, 5, 2017. Crossref

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