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+## Copyright (C) 2000, 2001, 2004, 2005 Gabriele Pannocchia.
+##
+## This file is part of Octave.
+##
+## Octave is free software; you can redistribute it and/or modify it
+## under the terms of the GNU General Public License as published by
+## the Free Software Foundation; either version 2, or (at your option)
+## any later version.
+##
+## Octave is distributed in the hope that it will be useful, but
+## WITHOUT ANY WARRANTY; without even the implied warranty of
+## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with Octave; see the file COPYING.  If not, write to the Free
+## Software Foundation, 59 Temple Place - Suite 330, Boston, MA
+## 02111-1307, USA.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {[@var{x}, @var{obj}, @var{info}, @var{lambda}] =} qp (@var{x0}, @var{H}, @var{q}, @var{A}, @var{b}, @var{lb}, @var{ub}, @var{A_lb}, @var{Ain}, @var{A_ub})
+## Solve the quadratic program
+## @ifinfo
+##
+## @example
+##      min 0.5 x'*H*x + x'*q
+##       x
+## @end example
+##
+## @end ifinfo
+## @iftex
+## @tex
+## @end tex
+## @end iftex
+## subject to
+## @ifinfo
+##
+## @example
+##      A*x = b
+##      lb <= x <= ub
+##      A_lb <= Ain*x <= A_ub
+## @end example
+## @end ifinfo
+## @iftex
+## @tex
+## @end tex
+## @end iftex
+##
+## @noindent
+## using a null-space active-set method.
+##
+## Any bound (@var{A}, @var{b}, @var{lb}, @var{ub}, @var{A_lb},
+## @var{A_ub}) may be set to the empty matrix (@code{[]}) if not
+## present.  If the initial guess is feasible the algorithm is faster.
+##
+## The value @var{info} is a structure with the following fields:
+## @table @code
+## @item solveiter
+## The number of iterations required to find the solution.
+## @item info
+## An integer indicating the status of the solution, as follows:
+## @table @asis
+## @item 0
+## The problem is feasible and convex.  Global solution found.
+## @item 1
+## The problem is not convex.  Local solution found.
+## @item 2
+## The problem is not convex and unbounded.
+## @item 3
+## Maximum number of iterations reached.
+## @item 6
+## The problem is infeasible.
+## @end table
+## @end table
+## @end deftypefn
+
+function [x, obj, INFO, lambda] = qp (x0, H, q, A, b, lb, ub, A_lb, A_in, A_ub)
+
+  if (nargin == 5 || nargin == 7 || nargin == 10)
+
+    ## Checking the quadratic penalty
+    n = issquare (H);
+    if (n == 0)
+      error ("qp: quadratic penalty matrix not square");
+    endif
+
+    n1 = issymmetric (H);
+    if (n1 == 0)
+      ## warning ("qp: quadratic penalty matrix not symmetric");
+      H = (H + H')/2;
+    endif
+
+    ## Checking the initial guess (if empty it is resized to the
+    ## right dimension and filled with 0)
+    if (isempty (x0))
+      x0 = zeros (n, 1);
+    elseif (length (x0) != n)
+      error ("qp: the initial guess has incorrect length");
+    endif
+
+    ## Linear penalty.
+    if (length (q) != n)
+      error ("qp: the linear term has incorrect length");
+    endif
+
+    ## Equality constraint matrices
+    if (isempty (A) || isempty(b))
+      n_eq = 0;
+      A = zeros (n_eq, n);
+      b = zeros (n_eq, 1);
+    else
+      [n_eq, n1] = size (A);
+      if (n1 != n)
+	error ("qp: equality constraint matrix has incorrect column dimension");
+      endif
+      if (length (b) != n_eq)
+	error ("qp: equality constraint matrix and vector have inconsistent dimension");
+      endif
+    endif
+
+    ## Bound constraints
+    Ain = zeros (0, n);
+    bin = zeros (0, 1);
+    n_in = 0;
+    if (nargin > 5)
+      if (! isempty (lb))
+	if (length(lb) != n)
+	  error ("qp: lower bound has incorrect length");
+	else
+	  Ain = [Ain; eye(n)];
+	  bin = [bin; lb];
+	endif
+      endif
+
+      if (! isempty (ub))
+	if (length (ub) != n)
+	  error ("qp: upper bound has incorrect length");
+	else
+	  Ain = [Ain; -eye(n)];
+	  bin = [bin; -ub];
+	endif
+      endif
+    endif
+
+    ## Inequality constraints
+    if (nargin > 7)
+      [dimA_in, n1] = size (A_in);
+      if (n1 != n)
+	error ("qp: inequality constraint matrix has incorrect column dimension");
+      else
+	if (! isempty (A_lb))
+	  if (length (A_lb) != dimA_in)
+	    error ("qp: inequality constraint matrix and lower bound vector inconsistent");
+	  else
+	    Ain = [Ain; A_in];
+	    bin = [bin; A_lb];
+	  endif
+	endif
+	if (! isempty (A_ub))
+	  if (length (A_ub) != dimA_in)
+	    error ("qp: inequality constraint matrix and upper bound vector inconsistent");
+	  else
+	    Ain = [Ain; -A_in];
+	    bin = [bin; -A_ub];
+	  endif
+	endif
+      endif
+    endif
+    n_in = length (bin);
+
+    ## Now we should have the following QP:
+    ##
+    ##   min_x  0.5*x'*H*x + x'*q
+    ##   s.t.   A*x = b
+    ##          Ain*x >= bin
+
+    ## Discard inequality constraints that have -Inf bounds since those
+    ## will never be active.
+    idx = isinf (bin) & bin < 0;
+    bin(idx) = [];
+    Ain(idx,:) = [];
+
+    ## Check if the initial guess is feasible.
+    rtol = sqrt (eps);
+
+    eq_infeasible = (n_eq > 0 && norm (A*x0-b) > rtol*(1+norm (b)));
+    in_infeasible = (n_in > 0 && any (Ain*x0-bin < -rtol*(1+norm (bin))));
+
+    info = 0;
+    if (eq_infeasible || in_infeasible)
+      ## The initial guess is not feasible.
+      ## First define xbar that is feasible with respect to the equality
+      ## constraints.
+      if (eq_infeasible)
+	if (rank (A) < n_eq)
+	  error ("qp: equality constraint matrix must be full row rank")
+	endif
+	xbar = pinv (A) * b;
+      else
+	xbar = x0;
+      endif
+
+      ## Check if xbar is feasible with respect to the inequality
+      ## constraints also.
+      if (n_in > 0)
+	res = Ain * xbar - bin;
+	if (any (res < -rtol * (1 + norm (bin))))
+	  ## xbar is not feasible with respect to the inequality
+	  ## constraints.  Compute a step in the null space of the
+	  ## equality constraints, by solving a QP.  If the slack is
+	  ## small, we have a feasible initial guess.  Otherwise, the
+	  ## problem is infeasible.
+	  if (n_eq > 0)
+	    Z = null (A);
+	    if (isempty (Z))
+	      ## The problem is infeasible because A is square and full
+	      ## rank, but xbar is not feasible.
+	      info = 6;
+	    endif
+	  endif
+
+	  if (info != 6)
+            ## Solve an LP with additional slack variables to find
+	    ## a feasible starting point.
+	    gamma = eye (n_in);
+	    if (n_eq > 0)
+	      Atmp = [Ain*Z, gamma];
+	      btmp = -res;
+	    else
+	      Atmp = [Ain, gamma];
+	      btmp = bin;
+	    endif
+	    ctmp = [zeros(n-n_eq, 1); ones(n_in, 1)];
+	    lb = [-Inf*ones(n-n_eq,1); zeros(n_in,1)];
+	    ub = [];
+	    ctype = repmat ("L", n_in, 1);
+	    [P, dummy, status] = glpk (ctmp, Atmp, btmp, lb, ub, ctype);
+
+	    if ((status == 180 || status == 181 || status == 151)
+		&& all (abs (P(n-n_eq+1:end)) < rtol * (1 + norm (btmp))))
+	      ## We found a feasible starting point
+	      if (n_eq > 0)
+		x0 = xbar + Z*P(1:n-n_eq)
+	      else
+		x0 = P(1:n);
+              endif
+	    else
+	      ## The problem is infeasible
+	      info = 6;
+	    endif
+	  endif
+	else
+	  ## xbar is feasible.  We use it a starting point.
+	  x0 = xbar;
+	endif
+      else
+	## xbar is feasible.  We use it a starting point.
+	x0 = xbar;
+      endif
+    endif
+
+    if (info == 0)
+      ## The initial (or computed) guess is feasible.
+      ## We call the solver.
+      maxit = 100;
+      [x, lambda, info, iter] = __qp__ (x0, H, q, A, b, Ain, bin, maxit);
+    else
+      iter = 0;
+      x = x0;
+      lambda = [];
+    endif
+    obj = 0.5 * x' * H * x + q' * x;
+    INFO.solveiter = iter;
+    INFO.info = info;
+
+  else
+    usage ("[x, obj, info, lambda] = qp (x0, H, q, A, b, lb, ub, A_lb, Ain, A_ub)");
+  endif
+
+endfunction