/// <summary>
/// Optional function for setting scaling parameter for the NLP.
/// This corresponds to the get_scaling_parameters method in TNLP.
/// If the pointers x_scaling or g_scaling are null, then no scaling
/// for x resp. g is done.
/// </summary>
/// <param name="obj_scaling">Scaling of the objective function</param>
/// <param name="x_scaling">Scaling of the problem variables</param>
/// <param name="g_scaling">Scaling of the constraint functions</param>
/// <returns>true if scaling succeeded, false otherwise</returns>
public bool SetScaling(double obj_scaling, double[] x_scaling, double[] g_scaling)
{
return(IsInitialized &&
AddOption("nlp_scaling_method", "user-scaling") &&
IpoptAdapter.SetIpoptProblemScaling(m_problem, obj_scaling, x_scaling, g_scaling) ==
IpoptBoolType.True);
}
public void IpoptSolve_SpecifiedStartGuess_YieldsExpectedOptimalVariables()
{
var actual = new[] { 10.0, 10.0, 10.0 };
double obj;
var expected = new[] { 24.0, 12.0, 12.0 };
IpoptAdapter.IpoptSolve(_instance, actual, null, out obj, null, null, null, IntPtr.Zero);
CollectionAssert.AreEqual(expected, actual, new DoubleComparer(1.0e-5));
}
public void IpoptSolve_SpecifiedStartGuess_ReturnsSucceededStatus()
{
var x = new[] { 10.0, 10.0, 10.0 };
double obj;
const IpoptReturnCode expected = IpoptReturnCode.Solve_Succeeded;
var actual = IpoptAdapter.IpoptSolve(_instance, x, null, out obj, null, null, null, IntPtr.Zero);
Assert.AreEqual(expected, actual);
}
public void Setup()
{
_hs037 = new HS037();
_instance = IpoptAdapter.CreateIpoptProblem(_hs037._n, _hs037._x_L, _hs037._x_U, _hs037._m, _hs037._g_L,
_hs037._g_U, _hs037._nele_jac, _hs037._nele_hess, IpoptIndexStyle.C,
_hs037.eval_f, _hs037.eval_g, _hs037.eval_grad_f, _hs037.eval_jac_g,
_hs037.eval_h);
IpoptAdapter.AddIpoptStrOption(_instance, "hessian_approximation", "limited-memory");
IpoptAdapter.AddIpoptIntOption(_instance, "limited_memory_max_history", 5);
}
public IpoptReturnCode SolveProblem(double[] x, out double obj_val, double[] g, double[] mult_g,
double[] mult_x_L, double[] mult_x_U)
#endif
{
if (!IsInitialized)
{
obj_val = PositiveInfinity;
return(IpoptReturnCode.Problem_Not_Initialized);
}
return(IpoptAdapter.IpoptSolve(m_problem, x, g, out obj_val, mult_g, mult_x_L, mult_x_U, IntPtr.Zero));
}
public void IpoptSolve_SpecifiedStartGuess_YieldsExpectedOptimalObjectiveValue()
{
const double expected = -3456.0;
var x = new[] { 10.0, 10.0, 10.0 };
double actual;
IpoptAdapter.IpoptSolve(_instance, x, null, out actual, null, null, null, IntPtr.Zero);
Assert.AreEqual(expected, actual, 1.0e-3);
}
/// <summary>
/// Constructor for creating a new Ipopt Problem object using native
/// 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">Native callback function for evaluating objective function</param>
/// <param name="eval_g_cb">Native callback function for evaluating constraint functions</param>
/// <param name="eval_grad_f_cb">Native callback function for evaluating gradient of objective function</param>
/// <param name="eval_jac_g_cb">Native callback function for evaluating Jacobian of constraint functions</param>
/// <param name="eval_h_cb">Native 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,
Eval_F_CB eval_f_cb, Eval_G_CB eval_g_cb, Eval_Grad_F_CB eval_grad_f_cb, Eval_Jac_G_CB eval_jac_g_cb, Eval_H_CB eval_h_cb)
{
m_eval_f_cb = eval_f_cb;
m_eval_g_cb = eval_g_cb;
m_eval_grad_f_cb = eval_grad_f_cb;
m_eval_jac_g_cb = eval_jac_g_cb;
m_eval_h_cb = eval_h_cb;
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;
}
public void SetIntermediateCallback_CallbackFunctionDefined_CallbackFunctionCalled()
{
const bool expected = true;
IpoptAdapter.SetIntermediateCallback(_instance, _hs037.intermediate);
_hs037.hasIntermediateBeenCalled = false;
var x = new[] { 10.0, 10.0, 10.0 };
double obj;
IpoptAdapter.IpoptSolve(_instance, x, null, out obj, null, null, null, IntPtr.Zero);
var actual = _hs037.hasIntermediateBeenCalled;
Assert.AreEqual(expected, actual);
}
/// <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>
/// Dispose(bool disposing) executes in two distinct scenarios.
/// If disposing equals true, the method has been called directly
/// or indirectly by a user's code. Managed and unmanaged resources
/// can be disposed.
/// If disposing equals false, the method has been called by the
/// runtime from inside the finalizer and you should not reference
/// other objects. Only unmanaged resources can be disposed.
/// </summary>
/// <param name="disposing">true if Dispose method is explicitly called, false otherwise.</param>
protected virtual void Dispose(bool disposing)
{
if (!m_disposed)
{
if (m_problem != IntPtr.Zero)
{
IpoptAdapter.FreeIpoptProblem(m_problem);
}
if (disposing)
{
m_problem = IntPtr.Zero;
}
m_disposed = true;
}
}
/// <summary>
/// Constructor for creating a subclassed Ipopt Problem object using managed or
/// native function delegates. This is the preferred constructor when
/// subclassing IpoptProblem. Prerequisite is that the managed/native optimization
/// function delegates are implemented in the inheriting class.
/// 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="useNativeCallbackFunctions">If set to true, native callback functions are used to setup
/// the Ipopt problem; if set to false, managed callback functions are used.</param>
/// <param name="useHessianApproximation">If set to true, the Ipopt optimizer creates a limited memory
/// Hessian approximation and the eval_h (managed or native) method need not be implemented.
/// If set to false, an exact Hessian should be evaluated using the appropriate Hessian evaluation method.</param>
/// <param name="useIntermediateCallback">If set to true, the intermediate method (managed or native) will be called
/// after each full iteration. If false, the intermediate callback function will not be called.</param>
protected IpoptProblem(int n, double[] x_L, double[] x_U, int m, double[] g_L, double[] g_U, int nele_jac, int nele_hess,
bool useNativeCallbackFunctions = false, bool useHessianApproximation = false, bool useIntermediateCallback = false)
{
if (useNativeCallbackFunctions)
{
m_eval_f_cb = eval_f;
m_eval_g_cb = eval_g;
m_eval_grad_f_cb = eval_grad_f;
m_eval_jac_g_cb = eval_jac_g;
m_eval_h_cb = eval_h;
}
else
{
m_eval_f_cb = new ObjectiveEvaluator(eval_f).Evaluate;
m_eval_g_cb = new ConstraintsEvaluator(eval_g).Evaluate;
m_eval_grad_f_cb = new ObjectiveGradientEvaluator(eval_grad_f).Evaluate;
m_eval_jac_g_cb = new JacobianEvaluator(eval_jac_g).Evaluate;
m_eval_h_cb = new HessianEvaluator(eval_h).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);
if (useHessianApproximation)
{
AddOption("hessian_approximation", "limited-memory");
}
if (useIntermediateCallback)
{
if (useNativeCallbackFunctions)
{
SetIntermediateCallback((Intermediate_CB)intermediate);
}
else
{
SetIntermediateCallback((IntermediateDelegate)intermediate);
}
}
m_disposed = false;
}
/// <summary>
/// Setting a callback function for the "intermediate callback"
/// method in the optimizer. This gives control back to the user once
/// per iteration. If set, it provides the user with some
/// information on the state of the optimization. This can be used
/// to print some user-defined output. It also gives the user a way
/// to terminate the optimization prematurely. If the callback
/// method returns false, Ipopt will terminate the optimization.
/// Calling this set method to set the CB pointer to null disables
/// the intermediate callback functionality.
/// </summary>
/// <param name="intermediate_cb">Native intermediate callback function</param>
/// <returns>true if the callback function could be set successfully, false otherwise</returns>
public bool SetIntermediateCallback(Intermediate_CB intermediate_cb)
{
return(IsInitialized &&
IpoptAdapter.SetIntermediateCallback(m_problem, m_intermediate_cb = intermediate_cb) == IpoptBoolType.True);
}
/// <summary>
/// Setting a callback function for the "intermediate callback"
/// method in the optimizer. This gives control back to the user once
/// per iteration. If set, it provides the user with some
/// information on the state of the optimization. This can be used
/// to print some user-defined output. It also gives the user a way
/// to terminate the optimization prematurely. If the callback
/// method returns false, Ipopt will terminate the optimization.
/// Calling this set method to set the CB pointer to null disables
/// the intermediate callback functionality.
/// </summary>
/// <param name="intermediate_cb">Managed intermediate callback function</param>
/// <returns>true if the callback function could be set successfully, false otherwise</returns>
public bool SetIntermediateCallback(IntermediateDelegate intermediate_cb)
{
return(IsInitialized && IpoptAdapter.SetIntermediateCallback(
m_problem, m_intermediate_cb = new IntermediateReporter(intermediate_cb).Report) == IpoptBoolType.True);
}
/// <summary>
/// Method for opening an output file for a given name with given print level.
/// </summary>
/// <param name="file_name">Name of output file</param>
/// <param name="print_level">Level of printed information</param>
/// <returns>False, if there was a problem opening the file.</returns>
public bool OpenOutputFile(string file_name, int print_level)
{
return(IsInitialized && IpoptAdapter.OpenIpoptOutputFile(m_problem, file_name, print_level) == IpoptBoolType.True);
}
/// <summary>
/// Function for adding an integer option.
/// </summary>
/// <param name="keyword">Name of option</param>
/// <param name="val">Integer value of option</param>
/// <returns>true if setting option succeeded, false if the option could not be set (e.g., if keyword is unknown)</returns>
public bool AddOption(string keyword, int val)
{
return(IsInitialized && IpoptAdapter.AddIpoptIntOption(m_problem, keyword, val) == IpoptBoolType.True);
}
public void Teardown()
{
IpoptAdapter.FreeIpoptProblem(_instance);
_hs037 = null;
}
