From 29e8e8bbd43892c7fa146c165fdf128f786d6a7b Mon Sep 17 00:00:00 2001 From: Harpreet Date: Mon, 2 Nov 2015 16:20:08 +0530 Subject: README.rst added --- help/en_US/scilab_en_US_help/qpipopt.html | 20 ++++++++++++++------ 1 file changed, 14 insertions(+), 6 deletions(-) (limited to 'help/en_US/scilab_en_US_help/qpipopt.html') diff --git a/help/en_US/scilab_en_US_help/qpipopt.html b/help/en_US/scilab_en_US_help/qpipopt.html index fba4521..6659f44 100644 --- a/help/en_US/scilab_en_US_help/qpipopt.html +++ b/help/en_US/scilab_en_US_help/qpipopt.html @@ -20,7 +20,7 @@ - qpipopt_mat >> + qpipoptmat >> @@ -38,6 +38,8 @@

Calling Sequence

xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB)
+xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0)
+xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0,param)
 [xopt,fopt,exitflag,output,lamda] = qpipopt( ... )

Parameters

@@ -48,17 +50,21 @@
Q :

a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.

p : -

a 1 x n matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem

+

a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem

LB : -

a 1 x n matrix of doubles, where n is number of variables, contains lower bounds of the variables.

+

a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.

UB : -

a 1 x n matrix of doubles, where n is number of variables, contains upper bounds of the variables.

+

a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.

conMatrix :

a m x n matrix of doubles, where n is number of variables and m is number of constraints, contains matrix representing the constraint matrix

conLB :

a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints.

conUB :

a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints.

+
x0 : +

a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables.

+
param : +

a list containing the the parameters to be set.

xopt :

a 1xn matrix of doubles, the computed solution of the optimization problem.

fopt : @@ -92,7 +98,9 @@ find the minimum of f(x) such that

p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6); nbVar = 6; nbCon = 5; -[xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
+x0 = repmat(0,nbVar,1); +param = list("MaxIter", 300, "CpuTime", 100); +[xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param)

Examples

//Find the value of x that minimize following function
@@ -130,7 +138,7 @@ find the minimum of f(x) such that
- qpipopt_mat >> + qpipoptmat >>
-- cgit