# CobylaOptimizer¶

class CobylaOptimizer(rhobeg=1.0, rhoend=0.0001, maxfun=1000, disp=None, catol=0.0002)[source]

The SciPy COBYLA optimizer wrapped as an Qiskit `OptimizationAlgorithm`.

This class provides a wrapper for `scipy.optimize.fmin_cobyla` (https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.optimize.fmin_cobyla.html) to be used within the optimization module. The arguments for `fmin_cobyla` are passed via the constructor.

Examples

```>>> from qiskit.optimization.problems import QuadraticProgram
>>> from qiskit.optimization.algorithms import CobylaOptimizer
>>> # specify problem here
>>> optimizer = CobylaOptimizer()
>>> result = optimizer.solve(problem)
```

Initializes the CobylaOptimizer.

This initializer takes the algorithmic parameters of COBYLA and stores them for later use of `fmin_cobyla` when `solve()` is invoked. This optimizer can be applied to find a (local) optimum for problems consisting of only continuous variables.

Parameters
• rhobeg (`float`) – Reasonable initial changes to the variables.

• rhoend (`float`) – Final accuracy in the optimization (not precisely guaranteed). This is a lower bound on the size of the trust region.

• disp (`Optional`[`int`]) – Controls the frequency of output; 0 implies no output. Feasible values are {0, 1, 2, 3}.

• maxfun (`int`) – Maximum number of function evaluations.

• catol (`float`) – Absolute tolerance for constraint violations.

Methods

 Checks whether a given problem can be solved with this optimizer. Checks whether a given problem can be solved with the optimizer implementing this method. `CobylaOptimizer.solve`(problem) Tries to solves the given problem using the optimizer.