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Conference rusure::math

Title:Mathematics at DEC
Moderator:RUSURE::EDP
Created:Mon Feb 03 1986
Last Modified:Fri Jun 06 1997
Last Successful Update:Fri Jun 06 1997
Number of topics:2083
Total number of notes:14613

1645.0. "Crux Mathematicorum 1742" by BEING::EDP (Always mount a scratch monkey.) Wed Jul 15 1992 13:52

    Here's a problem from _Crux Mathematicorum_.
    
    
    				-- edp
    
    
    1742. Proposed by Murray S. Klamkin, University of Alberta.
    
    Let 1 <= r < n be integers and x[r+1], x[r+2], . . ., x[n] be given
    positive real numbers.  Find positive x[1], x[2], . . ., x[r] so as to
    minimize the sum
    
    	S = sum x[i]/x[j]
    
    taken over all i and j in { 1, 2, 3, . . ., n } with i != j.
    
    (This problem is due to Byron Calhoun, a high school student in McLean,
    Virginia.  It appeared, with solution, in a science project of his.)
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1645.1SSAG::LARYLaughter &amp; hope &amp; a sock in the eyeThu Jul 16 1992 00:1713
This is equivalent to minimizing

	a*sum(Xi) + b*sum(1/Xi) + sum(Xi)*sum(1/Xi)

where the sums run from 1 to r, and

	a = sum(1/Xi) for i = r+1 to n
	b = sum(Xi)   for i = r+1 to n

Obviously if r = 1 then the (single) new x1 that minimizes the desired sum
is x1 = sqrt(b/a), and in fact you can't go too far wrong in the general
case by setting all the Xi equal to sqrt(b/a), but I don't think that's the
general minimum... 
1645.2DESIR::BUCHANANFri Jul 17 1992 09:4732
	We want to minimize:

	f = sum(Xi) * sum(1/Xi) where sums are from 1..n.

	df/dXj = sum(1/Xi) - sum(Xi)/Xj^2 for j=1..r.

	If df/dxj = 0, then:
	Xj^2 = sum(Xi)/sum(1/Xi) for j = 1..r.
ie. Xj = X for j=1...r.
	Let sum(j=r+1..n)(Xi) = a
	Let sum(j=r+1..n)(1/Xi) = b

	rX^2 = (a+rX)/(b+r/X)
=>	brX^2 + (r^2-r)X - a = 0

=>	X = [1-r +/- _/[(1-r)^2 + 4ab/r]]/2b

	But is this unique extremum minimal?   Since r < n, if we allow any
X_j to tend to zero or infinity, the value of f will go to infinity.   So
all boundaries to the domain are maxima.   I could say loosely that "by
elimination" the unique finite extremum that we've found must be a minimum,
but the right approach is to show that M, the matrix of second derivatives, is
+ve definite.

	The diagonal terms are:
-2/Xj^2 + 2*(a+sum(Xi))/Xj^3
	while the off-diagonal terms are:
-1/Xj^2 -1/Xk^2

	Is there anyone who can see that it's "obvious" that A is +ve definite?

Andrew.
1645.3final tidy-upDESIR::BUCHANANFri Jul 17 1992 11:5314
>	The diagonal terms are:
>	-2/Xj^2 + 2*(a+sum(Xi))/Xj^3
>	while the off-diagonal terms are:
>	-1/Xj^2 -1/Xk^2
>
>	Is there anyone who can see that it's "obvious" that M is +ve definite?

	Yes, it's obvious.   Xj = X, for j=1..r.

	If you take some random vector p = (p1..pr)', and compute p'Mp, you
get a*(something +ve) + (2/X^2)*[sum(1)sum(pi^2)-sum(pi)^2], and the stuff in
square brackets is +ve by the Schwartz inequality.   So that's it.

Andrew.