public class MinConNLPEx2 extends Object implements MinConNLP.Gradient
MinConNLP Example 2: Solves a general nonlinear programming problem with a user supplied gradient.
In this example, a general nonlinear programming problem is solved using a user-supplied gradient. The problem is as follows:$${\rm {min}} \,\, F(x) = (x_1 - 2)^2 + (x_2 - 1)^2$$
subject to
$$g_1(x) = x_1 - 2x_2 + 1 = 0$$
$$g_2(x) = -x_1^2 / 4 - x_2^2 + 1 \ge 0$$
Constructor and Description |
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MinConNLPEx2() |
Modifier and Type | Method and Description |
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double |
f(double[] x,
int iact,
boolean[] ierr)
Defines the objective function and constraints.
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void |
gradient(double[] x,
int iact,
double[] result)
Defines the gradients of the objective and the constraints.
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static void |
main(String[] args) |
public double f(double[] x, int iact, boolean[] ierr)
This function is called by MinConNLP
.
f
in interface MinConNLP.Function
x
- a double
array containing the variable valuesiact
- an int
specifying the return value. If
iact=0
this function returns the objective function
evaluated at x
. If iact
=\(1, 2, 3,...\), this
function returns the constraint with that index evaluated at
x
.ierr
- a boolean
array of length 1, where
ierr[0]=false
when no error or undesirable condition occurs
during evaluation, and ierr[0]=true
indicates some issue
during evaluationdouble
the value specified by iact
public void gradient(double[] x, int iact, double[] result)
gradient
in interface MinConNLP.Gradient
x
- a double
array containing the variable valuesiact
- an int
specifying what should be returned. If
iact=0
the gradient is returned evaluated at x
.
Otherwise, the gradient of the constraint with given index
iact=1,2,..
evaluated at x
is returned.result
- a double
array containing results on outputCopyright © 2020 Rogue Wave Software. All rights reserved.