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YeeKal
optimization

锥规划

YeeKal
"#optimization"

Conic Programming

max cTxs. t.dDxKAx=b

Here: - c,xRn - D:RnY linear, dY for some Euclidean space Y - KY is a closed convex cone - write xKy for yxK

锥规划的关注点是指约束条件为锥(相比于其它规划形式)

Second-order cone programming(SOCP)

Second-order cone:

Qn:={x=(x,t)Rn×R:tx,t0}

SOCP:

max cTxs. t.dDxQAx=b

where: $\mathcal{Q} = \mathcal{Q}{n1}\times \cdots \times \mathcal{Q}$

Observations:

  • case r=1 can be solved in closed-from
  • r2 is not so easy
  • LPSOCPSDP

Form transform

Second-order cone:

二阶是指二范数,比如对标准锥作仿射变换:

||Ax+b||2cTx+d(Ax+b,cTX+D)C

二次约束转化为锥约束:

XTAX+qTx+c0A12x+12A12q214qTAqc