Convex Optimization - Polar Cone



Let S be a non empty set in Rn Then, the polar cone of S denoted by S is given by S={pRn,pTx0xS}.

Remark

  • Polar cone is always convex even if S is not convex.

  • If S is empty set, S=Rn.

  • Polarity may be seen as a generalisation of orthogonality.

Let CRn then the orthogonal space of C, denoted by C={yRn:x,y=0xC}.

Lemma

Let S,S1 and S2 be non empty sets in Rn then the following statements are true −

  • S is a closed convex cone.

  • SS where S is a polar cone of S.

  • S1S2S2S1.

Proof

Step 1S={pRn,pTx0xS}

  • Let x1,x2SxT1x0 and xT2x0,xS

    For λ(0,1),[λx1+(1λ)x2]Tx=[(λx1)T+{(1λ)x2}T]x,xS

    =[λxT1+(1λ)xT2]x=λxT1x+(1λ)xT20

    Thus λx1+(1λ)x2S

    Therefore S is a convex set.

  • For λ0,pTx0,xS

    Therefore, λpTx0,

    (λp)Tx0

    λpS

    Thus, S is a cone.

  • To show S is closed, i.e., to show if pnp as n, then pS

    xS,pTnxpTx=(pnp)Tx

    As pnp as n(pnp)0

    Therefore pTnxpTx. But pTnx0,xS

    Thus, pTx0,xS

    pS

    Hence, S is closed.

Step 2S={qRn:qTp0,pS}

Let xS, then pS,pTx0xTp0xS

Thus, SS

Step 3S2={pRn:pTx0,xS2}

Since S1S2xS2xS1

Therefore, if ˆpS2,then ˆpTx0,xS2

ˆpTx0,xS1

ˆpTS1

S2S1

Theorem

Let C be a non empty closed convex cone, then C=C

Proof

C=C by previous lemma.

To prove : xCC

Let xC and let xC

Then by fundamental separation theorem, there exists a vector p0 and a scalar α such that pTyα,yC

Therefore, pTx>α

But since (y=0)C and pTyα,yCα0 and pTx>0

If pC, then there exists some ˉyC such that pTˉy>0 and pT(λˉy) can be made arbitrarily large by taking λ sufficiently large.

This contradicts with the fact that pTyα,yC

Therefore,pC

Since xC={q:qTp0,pC}

Therefore, xTp0pTx0

But pTx>α

Thus is contardiction.

Thus, xC

Hence C=C.

Advertisements