gemseo.problems.optimization.hock_schittkowski_71 module

Hock & Schittkowski problem 71.

This module implements the Hock & Schittkowski non-linear programming problem 71.

See: Willi Hock and Klaus Schittkowski. (1981) Test Examples for Nonlinear Programming Codes. Lecture Notes in Economics and Mathematical Systems Vol. 187, Springer-Verlag. Based on MATLAB code by Peter Carbonetto.

class HockSchittkowski71(initial_guess=(1.0, 5.0, 5.0, 1.0))

Bases: OptimizationProblem

Hock and Schittkowski problem 71.

Initialize the Hock Schittkowski 71 problem.

Parameters:

initial_guess (NumberArray) --

The initial guess for the optimal solution.

By default it is set to (1.0, 5.0, 5.0, 1.0).

static compute_equality_constraint(design_variables)

Compute the equality constraint function.

Parameters:

design_variables (NumberArray) -- The design variables vector.

Returns:

The equality constraint's value.

Return type:

NumberArray

static compute_equality_constraint_jacobian(design_variables)

Compute the equality constraint's Jacobian.

Parameters:

design_variables (NumberArray) -- The design variables vector.

Returns:

The Jacobian of the equality constraint function wrt the design variables.

Return type:

NumberArray

static compute_inequality_constraint(design_variables)

Compute the inequality constraint function.

Parameters:

design_variables (NumberArray) -- The design variables vector.

Returns:

The inequality constraint's value.

Return type:

NumberArray

static compute_inequality_constraint_jacobian(design_variables)

Compute the inequality constraint's Jacobian.

Parameters:

design_variables (NumberArray) -- The design variables vector.

Returns:

The Jacobian of the inequality constraint function wrt the design variables.

Return type:

NumberArray

static compute_objective(design_variables)

Compute the objectives of the Hock and Schittkowski 71 function.

Parameters:

design_variables (NumberArray) -- The design variables vector.

Returns:

The objective function value.

Return type:

NumberArray

static compute_objective_jacobian(design_variables)

Compute the Jacobian of objective function.

Parameters:

design_variables (NumberArray) -- The design variables vector.

Returns:

The gradient of the objective functions wrt the design variables.

Return type:

NumberArray

static get_solution()

Return the analytical solution of the problem.

Returns:

The theoretical optimum of the problem.

Return type:

tuple[NumberArray, NumberArray]