Variant of nontandard convex programming
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Rules for computing subdifferentials of convex operators with infinitesimal accuracy are derived. Applications to convex minimization problems are considered. The exposition is based on internal set theory, invented by \textit{E. Nelson} [Bull. Am. Math. Soc. 83, 1165-1198 (1977; Zbl 0373.02040)].
Convex programming, nonstandard convex programming, Other applications of nonstandard models (economics, physics, etc.), nonstandard analysis, infinitesimal subdifferentials, Methods of successive quadratic programming type, Nonstandard models, internal set theory, convex operators, infinitesimal accuracy, infinitesimally optimal solution, computation of subdifferentials
Convex programming, nonstandard convex programming, Other applications of nonstandard models (economics, physics, etc.), nonstandard analysis, infinitesimal subdifferentials, Methods of successive quadratic programming type, Nonstandard models, internal set theory, convex operators, infinitesimal accuracy, infinitesimally optimal solution, computation of subdifferentials
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