Minimization methods for non-differentiable functions
Minimization methods for non-differentiable functions
Certain questions in solving block nonlinear optimization problems with coupling variables
Cybernetics and Systems Analysis
On the development of software support for solving problems of optimal design of power boilers
Cybernetics and Systems Analysis
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An approach to reducing a constrained convex programming problem to an unconstrained optimization problem is considered. An initial internal feasible point is supposed to be specified. An equivalent unconstrained optimization problem is formulated in such a way that the calculated values of gradients (subgradients) of original functions do not violate the initial constraints. Properties of introduced functions are investigated. Convexity conditions are formulated for the unconstrained optimization problem. The results may by useful for the development of algorithms for solving constrained optimization problems.