From eb9ca1191c94059cd7adcf69805906c809fe9712 Mon Sep 17 00:00:00 2001 From: Harpreet Date: Tue, 29 Dec 2015 00:38:48 +0530 Subject: Bugs fixed 4 --- help/en_US/scilab_en_US_help/qpipopt.html | 40 +++++++++++++++---------------- 1 file changed, 20 insertions(+), 20 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 d4b6b3c..349bbc4 100644 --- a/help/en_US/scilab_en_US_help/qpipopt.html +++ b/help/en_US/scilab_en_US_help/qpipopt.html @@ -37,9 +37,9 @@

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 = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB)
+xopt = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0)
+xopt = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0,param)
 [xopt,fopt,exitflag,output,lamda] = qpipopt( ... )

Parameters

@@ -47,15 +47,15 @@

a double, number of variables

nbCon :

a double, number of constraints

-
Q : +
H :

a symmetric matrix of double, represents coefficients of quadratic in the quadratic problem.

-
p : +
f :

a vector of double, represents coefficients of linear in the quadratic problem

-
LB : +
lb :

a vector of double, contains lower bounds of the variables.

-
UB : +
ub :

a vector of double, contains upper bounds of the variables.

-
conMatrix : +
A :

a matrix of double, contains matrix representing the constraint matrix

conLB :

a vector of double, contains lower bounds of the constraints.

@@ -70,22 +70,22 @@
fopt :

a double, the function value at x.

exitflag : -

Integer identifying the reason the algorithm terminated.

+

Integer identifying the reason the algorithm terminated. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the qpipopt macro.

output : -

Structure containing information about the optimization. Right now it contains number of iteration.

+

Structure containing information about the optimization. This version only contains number of iterations

lambda :

Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.

Description

Search the minimum of a constrained linear quadratic optimization problem specified by : find the minimum of f(x) such that

-

-

We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++.

+

+

The routine calls Ipopt for solving the quadratic problem, Ipopt is a library written in C++.

Examples

//Find x in R^6 such that:
-conMatrix= [1,-1,1,0,3,1;
+A= [1,-1,1,0,3,1;
 -1,0,-3,-4,5,6;
 2,5,3,0,1,0
 0,1,0,1,2,-1;
@@ -94,13 +94,13 @@ find the minimum of f(x) such that

 conUB = [1;2;3;-1;2.5];
 lb=[-1000;-10000; 0; -1000; -1000; -1000];
 ub=[10000; 100; 1.5; 100; 100; 1000];
-//and minimize 0.5*x'*Q*x + p'*x with
-p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6);
+//and minimize 0.5*x'⋅H⋅x + f'⋅x with
+f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
 nbVar = 6;
 nbCon = 5;
 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)
+[xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB,x0,param)
 // Press ENTER to continue

Examples

@@ -111,16 +111,16 @@ find the minimum of f(x) such that

// –x1 + 2x2 ≤ 2 // 2x1 + x2 ≤ 3 // 0 ≤ x1, 0 ≤ x2. -Q = [1 -1; -1 2]; -p = [-2; -6]; -conMatrix = [1 1; -1 2; 2 1]; +H = [1 -1; -1 2]; +f = [-2; -6]; +A = [1 1; -1 2; 2 1]; conUB = [2; 2; 3]; conLB = [-%inf; -%inf; -%inf]; lb = [0; 0]; ub = [%inf; %inf]; nbVar = 2; nbCon = 3; -[xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
+[xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,H,f,lb,ub,A,conLB,conUB)

Authors

-- cgit