
Quotes:


where
x
is an
n dimensional vector and
f is a continuous real valued function.

minimize_{x}
c^{T}x 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)

minimize_{x}
x^{T}Q x +c^{T}x 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.

minimize_{X}
< C,X> subject to
Aop(X) = b, X psd

where
X
is a symmetric positive semidefinite matrix and
Aop is a linear transformation.

minimize_{x} f(x)
subject to
g_{k}(x) &le b_{k}, k = 1,...,m

where
x
is an
n dimensional vector and
f and
g_{k} are real valued
(sufficiently smooth) functions.

(from Luenberger text, 1969)
A nonconvex problem with strong duality (TRS pg 514)
Supplementary Information

the ubiquitous online source for
optimization.


Suggested Texts/References:
Back to Main Course Page
Start of
's
Home Page
(more
ambigrams)
Users' Home Pages on
orion.math,