optimization
锥规划
YeeKal
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"#optimization"
Conic Programming
max cTxs. t.d−Dx∈KAx=b
Here: - c,x∈Rn - D:Rn→Y linear, d∈Y for some Euclidean space Y - K⊆Y is a closed convex cone - write x⪯Ky for y−x∈K
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:t≥‖x‖,t≥0}
SOCP:
max cTxs. t.d−Dx∈QAx=b
where: $\mathcal{Q} = \mathcal{Q}{n1}\times \cdots \times \mathcal{Q}$
Observations:
- case r=1 can be solved in closed-from
- r≥2 is not so easy
- LP⊊SOCP⊊SDP
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||2≤cTx+d⟺(Ax+b,cTX+D)∈C
二次约束转化为锥约束:
XTAX+qTx+c≤0⟺‖A12x+12A−12q‖2≤14qTA−q−c