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Minimize a scalar function of one or more variables using the
Constrained Optimization BY Quadratic Approximations (COBYQA) algorithm [1]_.

.. versionadded:: 1.14.0

Options
-------
disp : bool
    Set to True to print information about the optimization procedure.
    Default is ``False``.
maxfev : int
    Maximum number of function evaluations. Default is ``500 * n``, where
    ``n`` is the number of variables.
maxiter : int
    Maximum number of iterations. Default is ``1000 * n``, where ``n`` is
    the number of variables.
f_target : float
    Target value for the objective function. The optimization procedure is
    terminated when the objective function value of a feasible point (see
    `feasibility_tol` below) is less than or equal to this target. Default
    is ``-numpy.inf``.
feasibility_tol : float
    Absolute tolerance for the constraint violation. Default is ``1e-8``.
initial_tr_radius : float
    Initial trust-region radius. Typically, this value should be in the
    order of one tenth of the greatest expected change to the variables.
    Default is ``1.0``.
final_tr_radius : float
    Final trust-region radius. It should indicate the accuracy required in
    the final values of the variables. If provided, this option overrides
    the value of `tol` in the `minimize` function. Default is ``1e-6``.
scale : bool
    Set to True to scale the variables according to the bounds. If True and
    if all the lower and upper bounds are finite, the variables are scaled
    to be within the range :math:`[-1, 1]`. If any of the lower or upper
    bounds is infinite, the variables are not scaled. Default is ``False``.

References
----------
.. [1] COBYQA
       https://www.cobyqa.com/stable/
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