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Diffstat (limited to 'help/en_US/qpipopt.xml')
| -rw-r--r-- | help/en_US/qpipopt.xml | 42 |
1 files changed, 21 insertions, 21 deletions
diff --git a/help/en_US/qpipopt.xml b/help/en_US/qpipopt.xml index 23e2c52..6dd578d 100644 --- a/help/en_US/qpipopt.xml +++ b/help/en_US/qpipopt.xml @@ -24,9 +24,9 @@ <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - 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( ... ) </synopsis> @@ -39,15 +39,15 @@ <listitem><para> a double, number of variables</para></listitem></varlistentry> <varlistentry><term>nbCon :</term> <listitem><para> a double, number of constraints</para></listitem></varlistentry> - <varlistentry><term>Q :</term> + <varlistentry><term>H :</term> <listitem><para> a symmetric matrix of double, represents coefficients of quadratic in the quadratic problem.</para></listitem></varlistentry> - <varlistentry><term>p :</term> + <varlistentry><term>f :</term> <listitem><para> a vector of double, represents coefficients of linear in the quadratic problem</para></listitem></varlistentry> - <varlistentry><term>LB :</term> + <varlistentry><term>lb :</term> <listitem><para> a vector of double, contains lower bounds of the variables.</para></listitem></varlistentry> - <varlistentry><term>UB :</term> + <varlistentry><term>ub :</term> <listitem><para> a vector of double, contains upper bounds of the variables.</para></listitem></varlistentry> - <varlistentry><term>conMatrix :</term> + <varlistentry><term>A :</term> <listitem><para> a matrix of double, contains matrix representing the constraint matrix</para></listitem></varlistentry> <varlistentry><term>conLB :</term> <listitem><para> a vector of double, contains lower bounds of the constraints.</para></listitem></varlistentry> @@ -62,9 +62,9 @@ <varlistentry><term>fopt :</term> <listitem><para> a double, the function value at x.</para></listitem></varlistentry> <varlistentry><term>exitflag :</term> - <listitem><para> Integer identifying the reason the algorithm terminated.</para></listitem></varlistentry> + <listitem><para> 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.</para></listitem></varlistentry> <varlistentry><term>output :</term> - <listitem><para> Structure containing information about the optimization. Right now it contains number of iteration.</para></listitem></varlistentry> + <listitem><para> Structure containing information about the optimization. This version only contains number of iterations</para></listitem></varlistentry> <varlistentry><term>lambda :</term> <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.</para></listitem></varlistentry> </variablelist> @@ -80,14 +80,14 @@ find the minimum of f(x) such that <latex> \begin{eqnarray} &\mbox{min}_{x} -& 1/2*x'*Q*x + p'*x \\ -& \text{subject to} & conLB \leq C(x) \leq conUB \\ +& 1/2⋅x^T⋅H⋅x + f^T⋅x \\ +& \text{subject to} & conLB \leq A⋅x \leq conUB \\ & & lb \leq x \leq ub \\ \end{eqnarray} </latex> </para> <para> -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++. </para> <para> </para> @@ -97,7 +97,7 @@ We are calling IPOpt for solving the quadratic problem, IPOpt is a library writt <title>Examples</title> <programlisting role="example"><![CDATA[ //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; @@ -106,13 +106,13 @@ conLB=[1;2;3;-%inf;-%inf]; 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 ]]></programlisting> @@ -128,16 +128,16 @@ param = list("MaxIter", 300, "CpuTime", 100); // –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) ]]></programlisting> </refsection> |