Rearrangement inequality

数学中的排列不等式及其应用

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排列不等式在数学中是一个基本的不等式，适用于任意实数的排列。本文详细阐述了该不等式的原理，并展示了其在算术平均与几何平均不等式、柯西-施瓦茨不等式以及切比雪夫求和不等式中的应用。通过证明过程，我们了解了如何利用排列不等式解决实际问题。

In mathematics, the rearrangement inequality^[1] states that

$x_ny_1 + \cdots + x_1y_n \le x_{\sigma (1)}y_1 + \cdots + x_{\sigma (n)}y_n \le x_1y_1 + \cdots + x_ny_n$

for every choice of real numbers

$x_1\le\cdots\le x_n\quad\text{and}\quad y_1\le\cdots\le y_n$

and every permutation

$x_{\sigma(1)},\dots,x_{\sigma(n)}\,$

of x₁, . . ., x_n. If the numbers are different, meaning that

$x_1<\cdots<x_n\quad\text{and}\quad y_1<\cdots<y_n,$

then the lower bound is attained only for the permutation which reverses the order, i.e. σ(i) = n − i + 1 for all i = 1, ..., n, and the upper bound is attained only for the identity, i.e. σ(i) = i for all i = 1, ..., n.

Note that the rearrangement inequality makes no assumptions on the signs of the real numbers.

Applications

Many famous inequalities can be proved by the rearrangement inequality, such as the arithmetic mean – geometric mean inequality, the Cauchy–Schwarz inequality, and Chebyshev's sum inequality.

Proof

The lower bound follows by applying the upper bound to

$-x_n\le\cdots\le-x_1.$

Therefore, it suffices to prove the upper bound. Since there are only finitely many permutations, there exists at least one for which

$x_{\sigma (1)}y_1 + \cdots + x_{\sigma (n)}y_n$

is maximal. In case there are several permutations with this property, let σ denote one with the highest number of fixed points.

We will now prove by contradiction, that σ has to be the identity (then we are done). Assume that σ is not the identity. Then there exists a j in {1, ..., n − 1} such that σ(j) ≠ j and σ(i) = i for all i in {1, ..., j − 1}. Hence σ(j) > j and there exists k in {j + 1, ..., n} with σ(k) = j. Now

$j<k\Rightarrow y_j\le y_k \qquad\text{and}\qquad j<\sigma(j)\Rightarrow x_j\le x_{\sigma(j)}.\quad(1)$

Therefore,

$0\le(x_{\sigma(j)}-x_j)(y_k-y_j). \quad(2)$

Expanding this product and rearranging gives

$x_{\sigma(j)}y_j+x_jy_k\le x_jy_j+x_{\sigma(j)}y_k\,, \quad(3)$

hence the permutation

$\tau(i):=\begin{cases}i&\text{for }i\in\{1,\ldots,j\},\\ \sigma(j)&\text{for }i=k,\\ \sigma(i)&\text{for }i\in\{j+1,\ldots,n\}\setminus\{k\},\end{cases}$

which arises from σ by exchanging the values σ(j) and σ(k), has at least one additional fixed point compared to σ, namely at j, and also attains the maximum. This contradicts the choice of σ.

$x_1<\cdots<x_n\quad\text{and}\quad y_1<\cdots<y_n,$

then we have strict inequalities at (1), (2), and (3), hence the maximum can only be attained by the identity, any other permutation σ cannot be optimal.

转载于:https://www.cnblogs.com/jiongjiong-mengmeng/archive/2013/04/14/3019710.html