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Diffstat (limited to 'macros/qpipopt.sci')
| -rw-r--r-- | macros/qpipopt.sci | 51 |
1 files changed, 40 insertions, 11 deletions
diff --git a/macros/qpipopt.sci b/macros/qpipopt.sci index e8c945a..33b31bb 100644 --- a/macros/qpipopt.sci +++ b/macros/qpipopt.sci @@ -26,16 +26,16 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) // f : a vector of double, represents coefficients of linear in the quadratic problem // lb : a vector of double, contains lower bounds of the variables. // ub : a vector of double, contains upper bounds of the variables. - // A : a matrix of double, contains matrix representing the constraint matrix + // A : a matrix of double, contains the constraint matrix // conLB : a vector of double, contains lower bounds of the constraints. // conUB : a vector of double, contains upper bounds of the constraints. // x0 : a vector of double, contains initial guess of variables. - // param : a list containing the the parameters to be set. + // param : a list containing the parameters to be set. // xopt : a vector of double, the computed solution of the optimization problem. - // fopt : a double, the function value at x. - // exitflag : A flag showing returned exit flag from Ipopt. 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 lsqlin macro. - // output : 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 bound multiplier and linear equality, inequality constraint multiplier. + // fopt : a double, the value of the function at x. + // exitflag : The exit status. See below for details. + // output : The structure consist of statistics about the optimization. See below for details. + // lambda : The structure consist of the Lagrange multipliers at the solution of problem. See below for details. // // Description // Search the minimum of a constrained linear quadratic optimization problem specified by : @@ -50,6 +50,35 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) // </latex> // // The routine calls Ipopt for solving the quadratic problem, Ipopt is a library written in C++. + // + // The exitflag allows to know the status of the optimization which is given back by Ipopt. + // <itemizedlist> + // <listitem>exitflag=0 : Optimal Solution Found </listitem> + // <listitem>exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal.</listitem> + // <listitem>exitflag=2 : Maximum CPU Time exceeded. Output may not be optimal.</listitem> + // <listitem>exitflag=3 : Stop at Tiny Step.</listitem> + // <listitem>exitflag=4 : Solved To Acceptable Level.</listitem> + // <listitem>exitflag=5 : Converged to a point of local infeasibility.</listitem> + // </itemizedlist> + // + // For more details on exitflag see the ipopt documentation, go to http://www.coin-or.org/Ipopt/documentation/ + // + // The output data structure contains detailed informations about the optimization process. + // It has type "struct" and contains the following fields. + // <itemizedlist> + // <listitem>output.iterations: The number of iterations performed during the search</listitem> + // <listitem>output.constrviolation: The max-norm of the constraint violation.</listitem> + // </itemizedlist> + // + // The lambda data structure contains the Lagrange multipliers at the end + // of optimization. In the current version the values are returned only when the the solution is optimal. + // It has type "struct" and contains the following fields. + // <itemizedlist> + // <listitem>lambda.lower: The Lagrange multipliers for the lower bound constraints.</listitem> + // <listitem>lambda.upper: The Lagrange multipliers for the upper bound constraints.</listitem> + // <listitem>lambda.eqlin: The Lagrange multipliers for the linear equality constraints.</listitem> + // <listitem>lambda.ineqlin: The Lagrange multipliers for the linear inequality constraints.</listitem> + // </itemizedlist> // // Examples // //Ref : example 14 : @@ -316,12 +345,14 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) end end - [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,A,conLB,conUB,lb,ub,x0,options); + [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,A,conLB,conUB,lb,ub,x0,options); xopt = xopt'; exitflag = status; - output = struct("Iterations" , []); - output.Iterations = iter; + output = struct("Iterations" , [], .. + "ConstrViolation" ,[]); + output.Iterations = iter; + output.ConstrViolation = max([0;(conLB'-A*xopt);(A*xopt - conUB');(lb'-xopt);(xopt-ub')]); lambda = struct("lower" , [], .. "upper" , [], .. "constraint" , []); @@ -331,7 +362,6 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) lambda.constraint = lmbda; select status - case 0 then printf("\nOptimal Solution Found.\n"); case 1 then @@ -367,5 +397,4 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) break; end - endfunction |