MODERNIZATION OF MEANS FOR ANALYSES AND SOLUTION OF NONLINEAR PROGRAMMING PROBLEMS
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The problems of optimization for nonlinear programming (NLP) with constraints inequalities are considered. Definition of condition-indicator as quantitative criterion of the properties of Lagrange function is justified. Application of indicator to increasing degree of completeness for system in NLP for finance and business problems with constraints inequalities are obtained. The new Lagrange function with square of each component of vector Lagrange multipliers for nonlinear objective function simultaneously with criterion-indicator as a source of additional equations is investigated. The conditions, in which the dimensionality of the vector of strategies and the number of constraints doesn’t effects on the uniqueness of the optimization problem solution is received and discussed.
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