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Quotes:
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where
x
is an
n dimensional vector and
f is a continuous real valued function.
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minimizex
cTx subject to
Ax = b, x &ge 0
|
where
x
is an
n dimensional vector and
A is an
m by
n matrix.
(NEOS Sample Submissions)
-
minimizex
xTQ x +cTx subject to
Ax = b, Bx &ge d
|
where
x
is an
n dimensional vector and
A is an
m by
n matrix and
B is a
p by
n matrix.
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minimizeX
< C,X> subject to
Aop(X) = b, X psd
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where
X
is a symmetric positive semidefinite matrix and
Aop is a linear transformation.
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minimizex f(x)
subject to
gk(x) &le bk, k = 1,...,m
|
where
x
is an
n dimensional vector and
f and
gk are real valued
(sufficiently smooth) functions.
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(from Luenberger text, 1969)
A nonconvex problem with strong duality (TRS pg 5-14)
Supplementary Information
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the ubiquitous online source for
optimization.
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Suggested Texts/References:
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