/// <summary>
/// Constructor for creating a new Ipopt Problem object. This function
/// returns an object that can be passed to the IpoptSolve call. It
/// contains the basic definition of the optimization problem, such
/// as number of variables and constraints, bounds on variables and
/// constraints, information about the derivatives, and the callback
/// function for the computation of the optimization problem
/// functions and derivatives. During this call, the options file
/// PARAMS.DAT is read as well.
/// </summary>
/// <param name="n">Number of optimization variables</param>
/// <param name="x_L">Lower bounds on variables. This array of size n is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// less or equal than the number specified by option 'nlp_lower_bound_inf' is interpreted to be minus infinity.</param>
/// <param name="x_U">Upper bounds on variables. This array of size n is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// greater or equal than the number specified by option 'nlp_upper_bound_inf' is interpreted to be plus infinity.</param>
/// <param name="m">Number of constraints.</param>
/// <param name="g_L">Lower bounds on constraints. This array of size m is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// less or equal than the number specified by option 'nlp_lower_bound_inf' is interpreted to be minus infinity.</param>
/// <param name="g_U">Upper bounds on constraints. This array of size m is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// greater or equal than the number specified by option 'nlp_upper_bound_inf' is interpreted to be plus infinity.</param>
/// <param name="nele_jac">Number of non-zero elements in constraint Jacobian.</param>
/// <param name="nele_hess">Number of non-zero elements in Hessian of Lagrangian.</param>
/// <param name="eval_f">Callback function for evaluating objective function</param>
/// <param name="eval_g">Callback function for evaluating constraint functions</param>
/// <param name="eval_grad_f">Callback function for evaluating gradient of objective function</param>
/// <param name="eval_jac_g">Callback function for evaluating Jacobian of constraint functions</param>
/// <param name="eval_h">Callback function for evaluating Hessian of Lagrangian function</param>
public Ipopt(int n, double[] x_L, double[] x_U, int m, double[] g_L, double[] g_U, int nele_jac, int nele_hess,
EvaluateObjectiveDelegate eval_f, EvaluateConstraintsDelegate eval_g, EvaluateObjectiveGradientDelegate eval_grad_f,
EvaluateJacobianDelegate eval_jac_g, EvaluateHessianDelegate eval_h)
{
unsafe
{
fixed(double *p_x_L = x_L, p_x_U = x_U, p_g_L = g_L, p_g_U = g_U)
{
m_eval_f = new ObjectiveEvaluator(eval_f).Evaluate;
m_eval_g = new ConstraintsEvaluator(eval_g).Evaluate;
m_eval_grad_f = new ObjectiveGradientEvaluator(eval_grad_f).Evaluate;
m_eval_jac_g = new JacobianEvaluator(eval_jac_g).Evaluate;
m_eval_h = new HessianEvaluator(eval_h).Evaluate;
m_intermediate = null;
m_problem = CreateIpoptProblem(n, p_x_L, p_x_U, m, p_g_L, p_g_U, nele_jac, nele_hess, 0,
m_eval_f, m_eval_g, m_eval_grad_f, m_eval_jac_g, m_eval_h);
if (m_problem == IntPtr.Zero)
{
throw new ArgumentException("Failed to initialize IPOPT problem");
}
}
}
m_disposed = false;
}
/// <summary>
/// Constructor for creating a new Ipopt Problem object using managed
/// function delegates. This function
/// initializes an object that can be passed to the IpoptSolve call. It
/// contains the basic definition of the optimization problem, such
/// as number of variables and constraints, bounds on variables and
/// constraints, information about the derivatives, and the callback
/// function for the computation of the optimization problem
/// functions and derivatives. During this call, the options file
/// ipopt.opt is read as well.
/// </summary>
/// <param name="n">Number of optimization variables</param>
/// <param name="x_L">Lower bounds on variables. This array of size n is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// less or equal than the number specified by option 'nlp_lower_bound_inf' is interpreted to be minus infinity.</param>
/// <param name="x_U">Upper bounds on variables. This array of size n is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// greater or equal than the number specified by option 'nlp_upper_bound_inf' is interpreted to be plus infinity.</param>
/// <param name="m">Number of constraints.</param>
/// <param name="g_L">Lower bounds on constraints. This array of size m is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// less or equal than the number specified by option 'nlp_lower_bound_inf' is interpreted to be minus infinity.</param>
/// <param name="g_U">Upper bounds on constraints. This array of size m is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// greater or equal than the number specified by option 'nlp_upper_bound_inf' is interpreted to be plus infinity.</param>
/// <param name="nele_jac">Number of non-zero elements in constraint Jacobian.</param>
/// <param name="nele_hess">Number of non-zero elements in Hessian of Lagrangian.</param>
/// <param name="eval_f_cb">Managed callback function for evaluating objective function</param>
/// <param name="eval_g_cb">Managed callback function for evaluating constraint functions</param>
/// <param name="eval_grad_f_cb">Managed callback function for evaluating gradient of objective function</param>
/// <param name="eval_jac_g_cb">Managed callback function for evaluating Jacobian of constraint functions</param>
/// <param name="eval_h_cb">Managed callback function for evaluating Hessian of Lagrangian function</param>
public IpoptProblem(int n, double[] x_L, double[] x_U, int m, double[] g_L, double[] g_U, int nele_jac, int nele_hess,
EvaluateObjectiveDelegate eval_f_cb, EvaluateConstraintsDelegate eval_g_cb, EvaluateObjectiveGradientDelegate eval_grad_f_cb,
EvaluateJacobianDelegate eval_jac_g_cb, EvaluateHessianDelegate eval_h_cb)
{
m_eval_f_cb = new ObjectiveEvaluator(eval_f_cb).Evaluate;
m_eval_g_cb = new ConstraintsEvaluator(eval_g_cb).Evaluate;
m_eval_grad_f_cb = new ObjectiveGradientEvaluator(eval_grad_f_cb).Evaluate;
m_eval_jac_g_cb = new JacobianEvaluator(eval_jac_g_cb).Evaluate;
m_eval_h_cb = new HessianEvaluator(eval_h_cb).Evaluate;
m_intermediate_cb = null;
m_problem = IpoptAdapter.CreateIpoptProblem(n, x_L, x_U, m, g_L, g_U, nele_jac, nele_hess, IpoptIndexStyle.C,
m_eval_f_cb, m_eval_g_cb, m_eval_grad_f_cb, m_eval_jac_g_cb, m_eval_h_cb);
m_disposed = false;
}
/// <summary>
/// Constructor for creating a new Ipopt Problem object using managed
/// function delegates. This function
/// initializes an object that can be passed to the IpoptSolve call. It
/// contains the basic definition of the optimization problem, such
/// as number of variables and constraints, bounds on variables and
/// constraints, information about the derivatives, and the callback
/// function for the computation of the optimization problem
/// functions and derivatives. During this call, the options file
/// ipopt.opt is read as well.
/// </summary>
/// <param name="n">Number of optimization variables</param>
/// <param name="x_L">Lower bounds on variables. This array of size n is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// less or equal than the number specified by option 'nlp_lower_bound_inf' is interpreted to be minus infinity.</param>
/// <param name="x_U">Upper bounds on variables. This array of size n is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// greater or equal than the number specified by option 'nlp_upper_bound_inf' is interpreted to be plus infinity.</param>
/// <param name="m">Number of constraints.</param>
/// <param name="g_L">Lower bounds on constraints. This array of size m is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// less or equal than the number specified by option 'nlp_lower_bound_inf' is interpreted to be minus infinity.</param>
/// <param name="g_U">Upper bounds on constraints. This array of size m is copied internally, so that the
/// caller can change the incoming data after return without that IpoptProblem is modified. Any value
/// greater or equal than the number specified by option 'nlp_upper_bound_inf' is interpreted to be plus infinity.</param>
/// <param name="nele_jac">Number of non-zero elements in constraint Jacobian.</param>
/// <param name="nele_hess">Number of non-zero elements in Hessian of Lagrangian.</param>
/// <param name="eval_f_cb">Managed callback function for evaluating objective function</param>
/// <param name="eval_g_cb">Managed callback function for evaluating constraint functions</param>
/// <param name="eval_grad_f_cb">Managed callback function for evaluating gradient of objective function</param>
/// <param name="eval_jac_g_cb">Managed callback function for evaluating Jacobian of constraint functions</param>
/// <param name="eval_h_cb">Managed callback function for evaluating Hessian of Lagrangian function</param>
public IpoptProblem(int n, double[] x_L, double[] x_U, int m, double[] g_L, double[] g_U, int nele_jac, int nele_hess,
EvaluateObjectiveDelegate eval_f_cb, EvaluateConstraintsDelegate eval_g_cb, EvaluateObjectiveGradientDelegate eval_grad_f_cb,
EvaluateJacobianDelegate eval_jac_g_cb, EvaluateHessianDelegate eval_h_cb)
{
m_eval_f_cb = new ObjectiveEvaluator(eval_f_cb).Evaluate;
m_eval_g_cb = new ConstraintsEvaluator(eval_g_cb).Evaluate;
m_eval_grad_f_cb = new ObjectiveGradientEvaluator(eval_grad_f_cb).Evaluate;
m_eval_jac_g_cb = new JacobianEvaluator(eval_jac_g_cb).Evaluate;
m_eval_h_cb = new HessianEvaluator(eval_h_cb).Evaluate;
m_intermediate_cb = null;
m_problem = IpoptAdapter.CreateIpoptProblem(n, x_L, x_U, m, g_L, g_U, nele_jac, nele_hess, IpoptIndexStyle.C,
m_eval_f_cb, m_eval_g_cb, m_eval_grad_f_cb, m_eval_jac_g_cb, m_eval_h_cb);
m_disposed = false;
}
internal ConstraintsEvaluator(EvaluateConstraintsDelegate eval_g_cb)
{
m_eval_g_cb = eval_g_cb;
}
internal ConstraintsEvaluator(EvaluateConstraintsDelegate eval_g_cb)
{
m_eval_g_cb = eval_g_cb;
}
internal ConstraintsEvaluator(EvaluateConstraintsDelegate eval_g)
{
m_eval_g = eval_g;
}
