$LastChangedDate: 2008-03-26 09:50:39 +0100 (Wed, 26 Mar 2008)
$
qld
linear quadratic programming solver
Calling Sequence
[x,lagr]=qld(Q,p,C,b,ci,cs,me [,tol])
[x,lagr,info]=qld(Q,p,C,b,ci,cs,me [,tol])
Parameters
Q
real positive definite symmetric matrix (dimension n
x n).
p
real (column) vector (dimension n)
C
real matrix (dimension (me + md) x
n)
b
RHS column vector (dimension (me +
md))
ci
column vector of lower-bounds (dimension
n). If there are no lower bound constraints, put
ci = []. If some components of
x are bounded from below, set the other
(unconstrained) values of ci to a very large
negative number (e.g. ci(j) =
-number_properties('huge').
cs
column vector of upper-bounds. (Same remarks as above).
me
number of equality constraints (i.e. C(1:me,:)*x =
b(1:me))
tol
:Floatting point number, required prÃ©cision.
x
optimal solution found.
lagr
vector of Lagrange multipliers. If lower and upper-bounds
ci,cs are provided, lagr has
n + me + md components and
lagr(1:n) is the Lagrange vector associated with
the bound constraints and lagr (n+1 : n + me +
md) is the Lagrange vector associated with the linear
constraints. (If an upper-bound (resp. lower-bound) constraint
i is active lagr(i) is > 0
(resp. <0). If no bounds are provided, lagr
has only me + md components.
info
integer, return the execution status instead of sending
errors.
info==1 : Too many iterations needed
info==2 : Accuracy insufficient to statisfy convergence
criterion
info==5 : Length of working array is too short
info==10: The constraints are inconsistent
Description
This function requires Q to be positive definite,
if it is not the case, one may use the The contributed toolbox "quapro".
Examples
See Also
qpsolve
optim
The contributed toolbox "quapro" may also be of interest, in
particular for singular Q.
Authors
K.Schittkowski
, University of Bayreuth, Germany
A.L. Tits and J.L. Zhou
, University of Maryland
Used Functions
ql0001.f in
modules/optimization/src/fortran/ql0001.f