Thread View: sci.math.num-analysis
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Started by Ossama Ismaeil
Fri, 06 Nov 1992 17:00
Re: Non-linear Inequality Constraint
Author: Ossama Ismaeil
Date: Fri, 06 Nov 1992 17:00
Date: Fri, 06 Nov 1992 17:00
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Hello !
In my previous posting I forgot to write one of the constraints.
Now, the problem can be described as
T
Min X X
S.T T
X A X <= 0
W X = C
where X is a vector , A is a square indefinite matrix, and W is a rectangular
matrix, and C is a constant vector.
This problem has both linear and non-linear equality and inequality
constraints.
Thanks,
Ossama
e-mail "ismaeil@qucis.queensu.ca"
Re: Non-linear Inequality Constraint
Author: David Handscomb
Date: Thu, 12 Nov 1992 18:18
Date: Thu, 12 Nov 1992 18:18
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In article <1992Nov6.170030.8063@qucis.queensu.ca> ismaeil@qucis.queensu.ca (Ossama Ismaeil) writes:
>
> Now, the problem can be described as
>
> T
> Min X X
>
> S.T T
> X A X <= 0
>
> W X = C
>
> where X is a vector , A is a square indefinite matrix, and W is a rectangular
> matrix, and C is a constant vector.
>
(Assume that A is symmetric and W is of maximal rank.)
Write Y = W^T (W W^T)^{-1} C. If Y^T A Y <= 0, then X = Y is the answer.
Otherwise, the answer will have X^T A X = 0.
Let Q be a rectangular matrix whose rows are are maximal set of orthonormal
vectors orthogonal to the rows of W. Then W X = C if and only if X is of the
form Y + Q Z, where the vector Z is in 1-1 correspondence with X.
So we want to minimize X^T X - Y^T Y = Z^T Z given that
X^T A X = Z^T Q^T A Q Z + 2 Y^T A Q Z + Y^T A Y = 0.
Find the eigensystem of (Q^T A Q) and expand Z in terms of the eigenvectors.
Then we can transform the problem into minimizing Sum_i (z_i^2) given that
Sum_i (a_i z_i^2) + 2 Sum_i (b_i z_i) + c = 0.
The solution to this is z_i = lambda b_i / (1 - lambda a_i), where lambda is
one of the roots of a polynomial equation, got by substituting this z_i into
the given condition. Hence Z, hence X.
David Handscomb
(dch@comlab.ox.ac.uk)
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