Minimum distance between sequence a and all permutations of another sequence b












2














Let $a$ and $b$ be finite sequences of length $n$, i.e. $a=(a_1,a_2,...,a_n), b=(b_1,b_2,...,b_n)$. I want to calculate the minimum of the distances (in an Lp norm) between $a$ and all permutations of $b$. Let $Pi_n$ be the space of all permutations of $n$ numbers, then I am looking for



$d = text{min}_{piinPi_n} ||a - (b_{pi(1)},b_{pi(2)},...,b_{pi(n)})||_p$



Is there an efficient method or optimization algorithm (something better than trying out all $n!$ permutations of b) to calculate $d$ and find the corresponding permutation $pi$?










share|cite|improve this question


















  • 4




    You might find this question helpful! stackoverflow.com/questions/54041397/…
    – Calvin Godfrey
    Jan 4 at 19:55










  • Calvin's linked post answers your question for $p=2$. I suspect that for any $L_p$ norm, the answer will be the same.
    – Omnomnomnom
    Jan 4 at 20:03






  • 1




    @Omnomnomnom I strongly doubt that. They are clearly not identical for the $L_infty$ norm.
    – LinAlg
    Jan 4 at 20:04






  • 1




    @LinAlg I don't think I see what you mean. Is there an example of a list $b$ sorted in ascending order, and a list $a$ such that you can do better than putting $a$ in ascending order?
    – Omnomnomnom
    Jan 4 at 20:11










  • thanks - and it's funny that the same question got asked (almost) at the same time!
    – appletree
    Jan 5 at 12:26
















2














Let $a$ and $b$ be finite sequences of length $n$, i.e. $a=(a_1,a_2,...,a_n), b=(b_1,b_2,...,b_n)$. I want to calculate the minimum of the distances (in an Lp norm) between $a$ and all permutations of $b$. Let $Pi_n$ be the space of all permutations of $n$ numbers, then I am looking for



$d = text{min}_{piinPi_n} ||a - (b_{pi(1)},b_{pi(2)},...,b_{pi(n)})||_p$



Is there an efficient method or optimization algorithm (something better than trying out all $n!$ permutations of b) to calculate $d$ and find the corresponding permutation $pi$?










share|cite|improve this question


















  • 4




    You might find this question helpful! stackoverflow.com/questions/54041397/…
    – Calvin Godfrey
    Jan 4 at 19:55










  • Calvin's linked post answers your question for $p=2$. I suspect that for any $L_p$ norm, the answer will be the same.
    – Omnomnomnom
    Jan 4 at 20:03






  • 1




    @Omnomnomnom I strongly doubt that. They are clearly not identical for the $L_infty$ norm.
    – LinAlg
    Jan 4 at 20:04






  • 1




    @LinAlg I don't think I see what you mean. Is there an example of a list $b$ sorted in ascending order, and a list $a$ such that you can do better than putting $a$ in ascending order?
    – Omnomnomnom
    Jan 4 at 20:11










  • thanks - and it's funny that the same question got asked (almost) at the same time!
    – appletree
    Jan 5 at 12:26














2












2








2


0





Let $a$ and $b$ be finite sequences of length $n$, i.e. $a=(a_1,a_2,...,a_n), b=(b_1,b_2,...,b_n)$. I want to calculate the minimum of the distances (in an Lp norm) between $a$ and all permutations of $b$. Let $Pi_n$ be the space of all permutations of $n$ numbers, then I am looking for



$d = text{min}_{piinPi_n} ||a - (b_{pi(1)},b_{pi(2)},...,b_{pi(n)})||_p$



Is there an efficient method or optimization algorithm (something better than trying out all $n!$ permutations of b) to calculate $d$ and find the corresponding permutation $pi$?










share|cite|improve this question













Let $a$ and $b$ be finite sequences of length $n$, i.e. $a=(a_1,a_2,...,a_n), b=(b_1,b_2,...,b_n)$. I want to calculate the minimum of the distances (in an Lp norm) between $a$ and all permutations of $b$. Let $Pi_n$ be the space of all permutations of $n$ numbers, then I am looking for



$d = text{min}_{piinPi_n} ||a - (b_{pi(1)},b_{pi(2)},...,b_{pi(n)})||_p$



Is there an efficient method or optimization algorithm (something better than trying out all $n!$ permutations of b) to calculate $d$ and find the corresponding permutation $pi$?







linear-algebra combinatorics optimization combinations discrete-optimization






share|cite|improve this question













share|cite|improve this question











share|cite|improve this question




share|cite|improve this question










asked Jan 4 at 19:48









appletreeappletree

283




283








  • 4




    You might find this question helpful! stackoverflow.com/questions/54041397/…
    – Calvin Godfrey
    Jan 4 at 19:55










  • Calvin's linked post answers your question for $p=2$. I suspect that for any $L_p$ norm, the answer will be the same.
    – Omnomnomnom
    Jan 4 at 20:03






  • 1




    @Omnomnomnom I strongly doubt that. They are clearly not identical for the $L_infty$ norm.
    – LinAlg
    Jan 4 at 20:04






  • 1




    @LinAlg I don't think I see what you mean. Is there an example of a list $b$ sorted in ascending order, and a list $a$ such that you can do better than putting $a$ in ascending order?
    – Omnomnomnom
    Jan 4 at 20:11










  • thanks - and it's funny that the same question got asked (almost) at the same time!
    – appletree
    Jan 5 at 12:26














  • 4




    You might find this question helpful! stackoverflow.com/questions/54041397/…
    – Calvin Godfrey
    Jan 4 at 19:55










  • Calvin's linked post answers your question for $p=2$. I suspect that for any $L_p$ norm, the answer will be the same.
    – Omnomnomnom
    Jan 4 at 20:03






  • 1




    @Omnomnomnom I strongly doubt that. They are clearly not identical for the $L_infty$ norm.
    – LinAlg
    Jan 4 at 20:04






  • 1




    @LinAlg I don't think I see what you mean. Is there an example of a list $b$ sorted in ascending order, and a list $a$ such that you can do better than putting $a$ in ascending order?
    – Omnomnomnom
    Jan 4 at 20:11










  • thanks - and it's funny that the same question got asked (almost) at the same time!
    – appletree
    Jan 5 at 12:26








4




4




You might find this question helpful! stackoverflow.com/questions/54041397/…
– Calvin Godfrey
Jan 4 at 19:55




You might find this question helpful! stackoverflow.com/questions/54041397/…
– Calvin Godfrey
Jan 4 at 19:55












Calvin's linked post answers your question for $p=2$. I suspect that for any $L_p$ norm, the answer will be the same.
– Omnomnomnom
Jan 4 at 20:03




Calvin's linked post answers your question for $p=2$. I suspect that for any $L_p$ norm, the answer will be the same.
– Omnomnomnom
Jan 4 at 20:03




1




1




@Omnomnomnom I strongly doubt that. They are clearly not identical for the $L_infty$ norm.
– LinAlg
Jan 4 at 20:04




@Omnomnomnom I strongly doubt that. They are clearly not identical for the $L_infty$ norm.
– LinAlg
Jan 4 at 20:04




1




1




@LinAlg I don't think I see what you mean. Is there an example of a list $b$ sorted in ascending order, and a list $a$ such that you can do better than putting $a$ in ascending order?
– Omnomnomnom
Jan 4 at 20:11




@LinAlg I don't think I see what you mean. Is there an example of a list $b$ sorted in ascending order, and a list $a$ such that you can do better than putting $a$ in ascending order?
– Omnomnomnom
Jan 4 at 20:11












thanks - and it's funny that the same question got asked (almost) at the same time!
– appletree
Jan 5 at 12:26




thanks - and it's funny that the same question got asked (almost) at the same time!
– appletree
Jan 5 at 12:26










2 Answers
2






active

oldest

votes


















2














If $pge 1$, then the minimum is attained by rearranging $b$ so that it is "order isomorphic" to $a$, meaning that $b_i-b_j$ has the same sign as $a_i-a_j$ for all $i,j$. To see this, suppose that $a_i<a_j$ and $b_i<b_j$. Using the convexity of the function $f(x)=|x|^p$, you can show that
$$
|a_i-b_i|^p+|a_j-b_j|^ple |a_i-b_j|^p+|a_j-b_i|^p
$$

Therefore, if $a_i$ is matched with $b_j$ and $a_j$ with $b_i$, it is more efficient to swap $b_i$ and $b_j$. This means if $b$ is optimal, it must have no such out-of-order matching.



When $p<1$, the function $|x^p|$ is no longer convex, so the same local swapping rule does not always hold. In fact, it is sometimes reversed. Here are some observations:




  • If $a_1<a_2<b_1<b_2$, then it is more efficient to match $a_1$ with $b_2$ and $a_2$ with $b_1$ (this is the opposite of the $pge 1$ case).


  • If $a_1<b_1<b_2<a_2$, then it is more efficient to match $a_1$ with $b_1$ and $a_2 $ with $b_2$ (this is the same as the $pge 1$ case).


  • If $a_1<b_1<a_2<b_2$, then the optimal matching depends on the values of $a_1,a_2,b_1$ and $b_2$. For example, when $a_2-b_1$ is very small, it is optimal to pair $a_1$ with $b_2$, but as $a_2-b_1$ increases to $infty$ while $b_1-a_1$ and $b_2-a_2$ remain constant, then eventually the opposite matching is better.



I am not sure if these observations translate into an algorithm.






share|cite|improve this answer





















  • These observations translate into the same algorithm given on the linked page for $p=2$ (from Ivo's answer)
    – Omnomnomnom
    Jan 5 at 20:03










  • That is, the algorithm works for $p in [1,infty]$
    – Omnomnomnom
    Jan 5 at 20:21



















1














An attempt to prove the inequality from Mike's answer. Feel free to correct this proof or fill in any gaps; I suspect that it's flawed.






Claim: if $a_1<a_2$ and $b_1<b_2$ are positive reals and $f$ is a non-negative, increasing, convex function over $[0,infty)$, then
$$
f(|a_1 - b_1|) + f(|a_2 - b_2|) leq f(|a_1 - b_2|) + f(|a_2 - b_1|)
$$




Proof: We note that $g(x) = f(|x|)$ is convex over $Bbb R$. So, for any $k>0$ and $a,b in Bbb R$, we have
$$
f(a - k) + f(b+k) geq f(a) + f(b)
$$

(This step seems shaky. I think this holds if $aleq b$ but not in general, which means that perhaps the rest of the proof needs to be broken into several cases)



It follows that
$$
f(|a_1 - b_2|) + f(|a_2 - b_1|) = \
f(|(a_1 - b_1) - (b_2 - b_1)|) + f(|(a_2 - b_2) + (b_2 - b_1)|) =\
g((a_1 - b_1) - (b_2 - b_1)) + g((a_2 - b_2) + (b_2 - b_1)) geq\
g(a_1 - b_1) + g(a_2 - b_2) = \
f(|a_1 - b_1|) + f(|a_2 - b_2|)
$$

as desired.






share|cite|improve this answer



















  • 1




    It holds for $a le b$ indeed (for $a>b$ the opposite holds). Proof: $exists tin(0,1): t(a-k) + (1-t) (b+k) = a$. Multiply by -1, add (a-k) and (b+k) then for the same $t$ we have $(1-t)(a-k) + t(b+k)=b$. Then due to convexity, $f(a)le tf(a-k) + (1-t) f(b+k)$ and $f(b)le (1-t) f(a-k) + t f(b+k)$. Summing both inequalities gives your inequality.
    – appletree
    Jan 5 at 23:21













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2 Answers
2






active

oldest

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2 Answers
2






active

oldest

votes









active

oldest

votes






active

oldest

votes









2














If $pge 1$, then the minimum is attained by rearranging $b$ so that it is "order isomorphic" to $a$, meaning that $b_i-b_j$ has the same sign as $a_i-a_j$ for all $i,j$. To see this, suppose that $a_i<a_j$ and $b_i<b_j$. Using the convexity of the function $f(x)=|x|^p$, you can show that
$$
|a_i-b_i|^p+|a_j-b_j|^ple |a_i-b_j|^p+|a_j-b_i|^p
$$

Therefore, if $a_i$ is matched with $b_j$ and $a_j$ with $b_i$, it is more efficient to swap $b_i$ and $b_j$. This means if $b$ is optimal, it must have no such out-of-order matching.



When $p<1$, the function $|x^p|$ is no longer convex, so the same local swapping rule does not always hold. In fact, it is sometimes reversed. Here are some observations:




  • If $a_1<a_2<b_1<b_2$, then it is more efficient to match $a_1$ with $b_2$ and $a_2$ with $b_1$ (this is the opposite of the $pge 1$ case).


  • If $a_1<b_1<b_2<a_2$, then it is more efficient to match $a_1$ with $b_1$ and $a_2 $ with $b_2$ (this is the same as the $pge 1$ case).


  • If $a_1<b_1<a_2<b_2$, then the optimal matching depends on the values of $a_1,a_2,b_1$ and $b_2$. For example, when $a_2-b_1$ is very small, it is optimal to pair $a_1$ with $b_2$, but as $a_2-b_1$ increases to $infty$ while $b_1-a_1$ and $b_2-a_2$ remain constant, then eventually the opposite matching is better.



I am not sure if these observations translate into an algorithm.






share|cite|improve this answer





















  • These observations translate into the same algorithm given on the linked page for $p=2$ (from Ivo's answer)
    – Omnomnomnom
    Jan 5 at 20:03










  • That is, the algorithm works for $p in [1,infty]$
    – Omnomnomnom
    Jan 5 at 20:21
















2














If $pge 1$, then the minimum is attained by rearranging $b$ so that it is "order isomorphic" to $a$, meaning that $b_i-b_j$ has the same sign as $a_i-a_j$ for all $i,j$. To see this, suppose that $a_i<a_j$ and $b_i<b_j$. Using the convexity of the function $f(x)=|x|^p$, you can show that
$$
|a_i-b_i|^p+|a_j-b_j|^ple |a_i-b_j|^p+|a_j-b_i|^p
$$

Therefore, if $a_i$ is matched with $b_j$ and $a_j$ with $b_i$, it is more efficient to swap $b_i$ and $b_j$. This means if $b$ is optimal, it must have no such out-of-order matching.



When $p<1$, the function $|x^p|$ is no longer convex, so the same local swapping rule does not always hold. In fact, it is sometimes reversed. Here are some observations:




  • If $a_1<a_2<b_1<b_2$, then it is more efficient to match $a_1$ with $b_2$ and $a_2$ with $b_1$ (this is the opposite of the $pge 1$ case).


  • If $a_1<b_1<b_2<a_2$, then it is more efficient to match $a_1$ with $b_1$ and $a_2 $ with $b_2$ (this is the same as the $pge 1$ case).


  • If $a_1<b_1<a_2<b_2$, then the optimal matching depends on the values of $a_1,a_2,b_1$ and $b_2$. For example, when $a_2-b_1$ is very small, it is optimal to pair $a_1$ with $b_2$, but as $a_2-b_1$ increases to $infty$ while $b_1-a_1$ and $b_2-a_2$ remain constant, then eventually the opposite matching is better.



I am not sure if these observations translate into an algorithm.






share|cite|improve this answer





















  • These observations translate into the same algorithm given on the linked page for $p=2$ (from Ivo's answer)
    – Omnomnomnom
    Jan 5 at 20:03










  • That is, the algorithm works for $p in [1,infty]$
    – Omnomnomnom
    Jan 5 at 20:21














2












2








2






If $pge 1$, then the minimum is attained by rearranging $b$ so that it is "order isomorphic" to $a$, meaning that $b_i-b_j$ has the same sign as $a_i-a_j$ for all $i,j$. To see this, suppose that $a_i<a_j$ and $b_i<b_j$. Using the convexity of the function $f(x)=|x|^p$, you can show that
$$
|a_i-b_i|^p+|a_j-b_j|^ple |a_i-b_j|^p+|a_j-b_i|^p
$$

Therefore, if $a_i$ is matched with $b_j$ and $a_j$ with $b_i$, it is more efficient to swap $b_i$ and $b_j$. This means if $b$ is optimal, it must have no such out-of-order matching.



When $p<1$, the function $|x^p|$ is no longer convex, so the same local swapping rule does not always hold. In fact, it is sometimes reversed. Here are some observations:




  • If $a_1<a_2<b_1<b_2$, then it is more efficient to match $a_1$ with $b_2$ and $a_2$ with $b_1$ (this is the opposite of the $pge 1$ case).


  • If $a_1<b_1<b_2<a_2$, then it is more efficient to match $a_1$ with $b_1$ and $a_2 $ with $b_2$ (this is the same as the $pge 1$ case).


  • If $a_1<b_1<a_2<b_2$, then the optimal matching depends on the values of $a_1,a_2,b_1$ and $b_2$. For example, when $a_2-b_1$ is very small, it is optimal to pair $a_1$ with $b_2$, but as $a_2-b_1$ increases to $infty$ while $b_1-a_1$ and $b_2-a_2$ remain constant, then eventually the opposite matching is better.



I am not sure if these observations translate into an algorithm.






share|cite|improve this answer












If $pge 1$, then the minimum is attained by rearranging $b$ so that it is "order isomorphic" to $a$, meaning that $b_i-b_j$ has the same sign as $a_i-a_j$ for all $i,j$. To see this, suppose that $a_i<a_j$ and $b_i<b_j$. Using the convexity of the function $f(x)=|x|^p$, you can show that
$$
|a_i-b_i|^p+|a_j-b_j|^ple |a_i-b_j|^p+|a_j-b_i|^p
$$

Therefore, if $a_i$ is matched with $b_j$ and $a_j$ with $b_i$, it is more efficient to swap $b_i$ and $b_j$. This means if $b$ is optimal, it must have no such out-of-order matching.



When $p<1$, the function $|x^p|$ is no longer convex, so the same local swapping rule does not always hold. In fact, it is sometimes reversed. Here are some observations:




  • If $a_1<a_2<b_1<b_2$, then it is more efficient to match $a_1$ with $b_2$ and $a_2$ with $b_1$ (this is the opposite of the $pge 1$ case).


  • If $a_1<b_1<b_2<a_2$, then it is more efficient to match $a_1$ with $b_1$ and $a_2 $ with $b_2$ (this is the same as the $pge 1$ case).


  • If $a_1<b_1<a_2<b_2$, then the optimal matching depends on the values of $a_1,a_2,b_1$ and $b_2$. For example, when $a_2-b_1$ is very small, it is optimal to pair $a_1$ with $b_2$, but as $a_2-b_1$ increases to $infty$ while $b_1-a_1$ and $b_2-a_2$ remain constant, then eventually the opposite matching is better.



I am not sure if these observations translate into an algorithm.







share|cite|improve this answer












share|cite|improve this answer



share|cite|improve this answer










answered Jan 5 at 17:48









Mike EarnestMike Earnest

20.7k11950




20.7k11950












  • These observations translate into the same algorithm given on the linked page for $p=2$ (from Ivo's answer)
    – Omnomnomnom
    Jan 5 at 20:03










  • That is, the algorithm works for $p in [1,infty]$
    – Omnomnomnom
    Jan 5 at 20:21


















  • These observations translate into the same algorithm given on the linked page for $p=2$ (from Ivo's answer)
    – Omnomnomnom
    Jan 5 at 20:03










  • That is, the algorithm works for $p in [1,infty]$
    – Omnomnomnom
    Jan 5 at 20:21
















These observations translate into the same algorithm given on the linked page for $p=2$ (from Ivo's answer)
– Omnomnomnom
Jan 5 at 20:03




These observations translate into the same algorithm given on the linked page for $p=2$ (from Ivo's answer)
– Omnomnomnom
Jan 5 at 20:03












That is, the algorithm works for $p in [1,infty]$
– Omnomnomnom
Jan 5 at 20:21




That is, the algorithm works for $p in [1,infty]$
– Omnomnomnom
Jan 5 at 20:21











1














An attempt to prove the inequality from Mike's answer. Feel free to correct this proof or fill in any gaps; I suspect that it's flawed.






Claim: if $a_1<a_2$ and $b_1<b_2$ are positive reals and $f$ is a non-negative, increasing, convex function over $[0,infty)$, then
$$
f(|a_1 - b_1|) + f(|a_2 - b_2|) leq f(|a_1 - b_2|) + f(|a_2 - b_1|)
$$




Proof: We note that $g(x) = f(|x|)$ is convex over $Bbb R$. So, for any $k>0$ and $a,b in Bbb R$, we have
$$
f(a - k) + f(b+k) geq f(a) + f(b)
$$

(This step seems shaky. I think this holds if $aleq b$ but not in general, which means that perhaps the rest of the proof needs to be broken into several cases)



It follows that
$$
f(|a_1 - b_2|) + f(|a_2 - b_1|) = \
f(|(a_1 - b_1) - (b_2 - b_1)|) + f(|(a_2 - b_2) + (b_2 - b_1)|) =\
g((a_1 - b_1) - (b_2 - b_1)) + g((a_2 - b_2) + (b_2 - b_1)) geq\
g(a_1 - b_1) + g(a_2 - b_2) = \
f(|a_1 - b_1|) + f(|a_2 - b_2|)
$$

as desired.






share|cite|improve this answer



















  • 1




    It holds for $a le b$ indeed (for $a>b$ the opposite holds). Proof: $exists tin(0,1): t(a-k) + (1-t) (b+k) = a$. Multiply by -1, add (a-k) and (b+k) then for the same $t$ we have $(1-t)(a-k) + t(b+k)=b$. Then due to convexity, $f(a)le tf(a-k) + (1-t) f(b+k)$ and $f(b)le (1-t) f(a-k) + t f(b+k)$. Summing both inequalities gives your inequality.
    – appletree
    Jan 5 at 23:21


















1














An attempt to prove the inequality from Mike's answer. Feel free to correct this proof or fill in any gaps; I suspect that it's flawed.






Claim: if $a_1<a_2$ and $b_1<b_2$ are positive reals and $f$ is a non-negative, increasing, convex function over $[0,infty)$, then
$$
f(|a_1 - b_1|) + f(|a_2 - b_2|) leq f(|a_1 - b_2|) + f(|a_2 - b_1|)
$$




Proof: We note that $g(x) = f(|x|)$ is convex over $Bbb R$. So, for any $k>0$ and $a,b in Bbb R$, we have
$$
f(a - k) + f(b+k) geq f(a) + f(b)
$$

(This step seems shaky. I think this holds if $aleq b$ but not in general, which means that perhaps the rest of the proof needs to be broken into several cases)



It follows that
$$
f(|a_1 - b_2|) + f(|a_2 - b_1|) = \
f(|(a_1 - b_1) - (b_2 - b_1)|) + f(|(a_2 - b_2) + (b_2 - b_1)|) =\
g((a_1 - b_1) - (b_2 - b_1)) + g((a_2 - b_2) + (b_2 - b_1)) geq\
g(a_1 - b_1) + g(a_2 - b_2) = \
f(|a_1 - b_1|) + f(|a_2 - b_2|)
$$

as desired.






share|cite|improve this answer



















  • 1




    It holds for $a le b$ indeed (for $a>b$ the opposite holds). Proof: $exists tin(0,1): t(a-k) + (1-t) (b+k) = a$. Multiply by -1, add (a-k) and (b+k) then for the same $t$ we have $(1-t)(a-k) + t(b+k)=b$. Then due to convexity, $f(a)le tf(a-k) + (1-t) f(b+k)$ and $f(b)le (1-t) f(a-k) + t f(b+k)$. Summing both inequalities gives your inequality.
    – appletree
    Jan 5 at 23:21
















1












1








1






An attempt to prove the inequality from Mike's answer. Feel free to correct this proof or fill in any gaps; I suspect that it's flawed.






Claim: if $a_1<a_2$ and $b_1<b_2$ are positive reals and $f$ is a non-negative, increasing, convex function over $[0,infty)$, then
$$
f(|a_1 - b_1|) + f(|a_2 - b_2|) leq f(|a_1 - b_2|) + f(|a_2 - b_1|)
$$




Proof: We note that $g(x) = f(|x|)$ is convex over $Bbb R$. So, for any $k>0$ and $a,b in Bbb R$, we have
$$
f(a - k) + f(b+k) geq f(a) + f(b)
$$

(This step seems shaky. I think this holds if $aleq b$ but not in general, which means that perhaps the rest of the proof needs to be broken into several cases)



It follows that
$$
f(|a_1 - b_2|) + f(|a_2 - b_1|) = \
f(|(a_1 - b_1) - (b_2 - b_1)|) + f(|(a_2 - b_2) + (b_2 - b_1)|) =\
g((a_1 - b_1) - (b_2 - b_1)) + g((a_2 - b_2) + (b_2 - b_1)) geq\
g(a_1 - b_1) + g(a_2 - b_2) = \
f(|a_1 - b_1|) + f(|a_2 - b_2|)
$$

as desired.






share|cite|improve this answer














An attempt to prove the inequality from Mike's answer. Feel free to correct this proof or fill in any gaps; I suspect that it's flawed.






Claim: if $a_1<a_2$ and $b_1<b_2$ are positive reals and $f$ is a non-negative, increasing, convex function over $[0,infty)$, then
$$
f(|a_1 - b_1|) + f(|a_2 - b_2|) leq f(|a_1 - b_2|) + f(|a_2 - b_1|)
$$




Proof: We note that $g(x) = f(|x|)$ is convex over $Bbb R$. So, for any $k>0$ and $a,b in Bbb R$, we have
$$
f(a - k) + f(b+k) geq f(a) + f(b)
$$

(This step seems shaky. I think this holds if $aleq b$ but not in general, which means that perhaps the rest of the proof needs to be broken into several cases)



It follows that
$$
f(|a_1 - b_2|) + f(|a_2 - b_1|) = \
f(|(a_1 - b_1) - (b_2 - b_1)|) + f(|(a_2 - b_2) + (b_2 - b_1)|) =\
g((a_1 - b_1) - (b_2 - b_1)) + g((a_2 - b_2) + (b_2 - b_1)) geq\
g(a_1 - b_1) + g(a_2 - b_2) = \
f(|a_1 - b_1|) + f(|a_2 - b_2|)
$$

as desired.







share|cite|improve this answer














share|cite|improve this answer



share|cite|improve this answer








answered Jan 5 at 20:33


























community wiki





Omnomnomnom









  • 1




    It holds for $a le b$ indeed (for $a>b$ the opposite holds). Proof: $exists tin(0,1): t(a-k) + (1-t) (b+k) = a$. Multiply by -1, add (a-k) and (b+k) then for the same $t$ we have $(1-t)(a-k) + t(b+k)=b$. Then due to convexity, $f(a)le tf(a-k) + (1-t) f(b+k)$ and $f(b)le (1-t) f(a-k) + t f(b+k)$. Summing both inequalities gives your inequality.
    – appletree
    Jan 5 at 23:21
















  • 1




    It holds for $a le b$ indeed (for $a>b$ the opposite holds). Proof: $exists tin(0,1): t(a-k) + (1-t) (b+k) = a$. Multiply by -1, add (a-k) and (b+k) then for the same $t$ we have $(1-t)(a-k) + t(b+k)=b$. Then due to convexity, $f(a)le tf(a-k) + (1-t) f(b+k)$ and $f(b)le (1-t) f(a-k) + t f(b+k)$. Summing both inequalities gives your inequality.
    – appletree
    Jan 5 at 23:21










1




1




It holds for $a le b$ indeed (for $a>b$ the opposite holds). Proof: $exists tin(0,1): t(a-k) + (1-t) (b+k) = a$. Multiply by -1, add (a-k) and (b+k) then for the same $t$ we have $(1-t)(a-k) + t(b+k)=b$. Then due to convexity, $f(a)le tf(a-k) + (1-t) f(b+k)$ and $f(b)le (1-t) f(a-k) + t f(b+k)$. Summing both inequalities gives your inequality.
– appletree
Jan 5 at 23:21






It holds for $a le b$ indeed (for $a>b$ the opposite holds). Proof: $exists tin(0,1): t(a-k) + (1-t) (b+k) = a$. Multiply by -1, add (a-k) and (b+k) then for the same $t$ we have $(1-t)(a-k) + t(b+k)=b$. Then due to convexity, $f(a)le tf(a-k) + (1-t) f(b+k)$ and $f(b)le (1-t) f(a-k) + t f(b+k)$. Summing both inequalities gives your inequality.
– appletree
Jan 5 at 23:21




















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