Definition
Given a real vector space X, a convex, real-valued function
defined on a convex cone, and an affine subspace defined by a set of affine constraints, a conic optimization problem is to find the point in for which the number is smallest. Examples of include the positive semidefinite matrices, the positive orthant for, and the second-order cone . Often is a linear function, in which case the conic optimization problem reduces to a semidefinite program, a linear program, and a second order cone program, respectively.
Read more about this topic: Conic Optimization
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