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According to the literature and the website provided by opfunu.name_based.Meyer, the global optimal solution of this problem should be (5.6096364710E-03, 6.1813463463E+03, 3.4522363462E+02). However, the global optimal solution of Meyer function in opfunu is incorrectly written as (5.6096364710e-3, 6.1813463463e2, 3.4522363462e2), and the second dimension is incorrectly reduced by 10 times.
Therefore, the boundary definition of Meyer function in opfunu is also wrong, and the real global optimal solution is not included in the boundary.
Since I haven't found the specific boundaries of the problem, I hope the author can give the correct boundary definition.
Steps To Reproduce
In the Mayer problem, the global optimal solution is incorrectly defined as 'self.x_global = np.array([5.6096364710e-3, 6.1813463463e2, 3.4522363462e2])'
And the bounds do not contain the correct global optimal solution
'self.check_ndim_and_bounds(ndim, bounds, np.array([[0., 1.], [100., 1000.], [100., 500.]]))'
Additional Information
No response
The text was updated successfully, but these errors were encountered:
Further agree that with the corrected global solution from the original source the second bounds need to have a larger range, something like [1000..10000.]
Feel free to make these changes and initiate a pull request.
Description of the bug
According to the literature and the website provided by opfunu.name_based.Meyer, the global optimal solution of this problem should be (5.6096364710E-03, 6.1813463463E+03, 3.4522363462E+02). However, the global optimal solution of Meyer function in opfunu is incorrectly written as (5.6096364710e-3, 6.1813463463e2, 3.4522363462e2), and the second dimension is incorrectly reduced by 10 times.



Therefore, the boundary definition of Meyer function in opfunu is also wrong, and the real global optimal solution is not included in the boundary.
Since I haven't found the specific boundaries of the problem, I hope the author can give the correct boundary definition.
Steps To Reproduce
In the Mayer problem, the global optimal solution is incorrectly defined as 'self.x_global = np.array([5.6096364710e-3, 6.1813463463e2, 3.4522363462e2])'
And the bounds do not contain the correct global optimal solution
'self.check_ndim_and_bounds(ndim, bounds, np.array([[0., 1.], [100., 1000.], [100., 500.]]))'
Additional Information
No response
The text was updated successfully, but these errors were encountered: