# Relation of $\max_P \; x^T \cdot Py$ and $\min_P \; \|x-Py\|_2$

Consider a permutation matrix $P$ and two vectors $x$, $v$ with 2-norm = 1 and all positive entries.

Are the optimal solutions $P^\ast$ of $\max_P \; (x^T \cdot Py)$ and $\min_P \; \|x-Py\|_2$ the same?

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Minimizing $\|x-Py\|^2_2=\|x\|^2_2+\|y\|^2-2(x^T\cdot Py)$ over $P$ is equivalent to maximizing $x^T\cdot Py$. –  Did Oct 26 '11 at 6:57

$$\|x-Py\|_2^2=\|x\|_2^2+\|Py\|_2^2-2x^T\cdot Py=2(1-x^T\cdot Py)$$
@Benjamin That approach works. In fact, you can fix one of the permutations arbitrarily, and optimize over the second permutation. (Note that $\| Px - Qy \| = \| x - P^{-1} Q y \|$.) –  Srivatsan Oct 26 '11 at 7:09