function [x,lambda,f,gradf,g,A,HessL] = sqp(prob,x,lambda);

% function [x,lambda,f,gradf,g,A,HessL] = sqp(prob,x,lambda);
%
% solves the problem
%
% minimize   f(x)
% subject to g_i(x) >= 0, i=1,...,m
%
% The input variable prob points to an m file that provides problem
% data for each iteration on the form
%
% [f,gradf,g,A,HessL] = ex512(x,lambda)
%
% where
%
% f           Objective function
% gradf       Objective function gradient
% g           Constraint function
% A           Constraint Jacobian
% HessL       Hessian of Lagrangian function
% ( HessL = Hessf - sum lambda(i) Hessg{i} )
%
% at a given point (x,lambda)



% Write your solver here. You may want to add additional input
% and/or output arguments and omit some of the output arguments.

% At each iteration, compute problem data for the problem specified
% by prob.

[f,gradf,g,A,HessL] = feval(prob,x,lambda);