Semidefinite Programing (SDP): Difference between revisions

Revision as of 13:12, 11 January 2016

Semidefinite programming (SDP) is a subfield of convex optimization concerned with the optimization of a linear objective function over the intersection of the cone of positive semidefinite matrices with an affine space.

Minimize [math]\displaystyle{ C.X \\ }[/math]

such that [math]\displaystyle{ A_i X=b_i,i=1,\dots,m \\ X \geq 0 }[/math]

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 Semidefinite programming (SDP) is a [[subfield]] of [[convex optimization]] concerned with the [[optimization]] of a [[linear objective function]] over the intersection of the cone of [[positive semidefinite matrices]] with an [[affine space]].
 * <B>Context:</B>
-** <p>It is an optimization problem of the form:<math>\\</math>Minimize <math>C.X \\</math> such that <math>A_i X=b_i,i=1,\dots,m \\ X \geq 0</math></p>
+** <p>It is an optimization problem of the form:
+Minimize <math>C.X \\</math>
+such that <math>A_i X=b_i,i=1,\dots,m \\ X \geq 0</math></p>