In this paper we consider min-max convex semi-infinite programming. To solve these problems we introduce a unified framework concerning Remez-type algorithms and integral methods coupled with penalty ...
A modified version of Generalized Programming is presented for solving convex programming problems. The procedure uses convenient linear approximations of the gradient of the dual in order to ...
Quadratic programming has a variety of applications, such as resource planning, portfolio optimization, and structural analysis. Download this technical whitepaper on the sparse convex quadratic ...
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