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---
title: CobylaOptimizer
description: API reference for qiskit.optimization.algorithms.CobylaOptimizer
in_page_toc_min_heading_level: 1
python_api_type: class
python_api_name: qiskit.optimization.algorithms.CobylaOptimizer
---
# qiskit.optimization.algorithms.CobylaOptimizer
<Class id="qiskit.optimization.algorithms.CobylaOptimizer" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.9/qiskit/optimization/algorithms/cobyla_optimizer.py" signature="CobylaOptimizer(rhobeg=1.0, rhoend=0.0001, maxfun=1000, disp=None, catol=0.0002, trials=1, clip=100.0)" modifiers="class">
The SciPy COBYLA optimizer wrapped as an Qiskit [`OptimizationAlgorithm`](qiskit.optimization.algorithms.OptimizationAlgorithm "qiskit.optimization.algorithms.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](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**
```python
>>> from qiskit.optimization.problems import QuadraticProgram
>>> from qiskit.optimization.algorithms import CobylaOptimizer
>>> problem = QuadraticProgram()
>>> # 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()`](#qiskit.optimization.algorithms.CobylaOptimizer.solve "qiskit.optimization.algorithms.CobylaOptimizer.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.
* **trials** (`int`) The number of trials for multi-start method. The first trial is solved with the initial guess of zero. If more than one trial is specified then initial guesses are uniformly drawn from `[lowerbound, upperbound]` with potential clipping.
* **clip** (`float`) Clipping parameter for the initial guesses in the multi-start method. If a variable is unbounded then the lower bound and/or upper bound are replaced with the `-clip` or `clip` values correspondingly for the initial guesses.
### \_\_init\_\_
<Function id="qiskit.optimization.algorithms.CobylaOptimizer.__init__" signature="__init__(rhobeg=1.0, rhoend=0.0001, maxfun=1000, disp=None, catol=0.0002, trials=1, clip=100.0)">
Initializes the CobylaOptimizer.
This initializer takes the algorithmic parameters of COBYLA and stores them for later use of `fmin_cobyla` when [`solve()`](#qiskit.optimization.algorithms.CobylaOptimizer.solve "qiskit.optimization.algorithms.CobylaOptimizer.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.
* **trials** (`int`) The number of trials for multi-start method. The first trial is solved with the initial guess of zero. If more than one trial is specified then initial guesses are uniformly drawn from `[lowerbound, upperbound]` with potential clipping.
* **clip** (`float`) Clipping parameter for the initial guesses in the multi-start method. If a variable is unbounded then the lower bound and/or upper bound are replaced with the `-clip` or `clip` values correspondingly for the initial guesses.
</Function>
## Methods
| | |
| -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------- |
| [`__init__`](#qiskit.optimization.algorithms.CobylaOptimizer.__init__ "qiskit.optimization.algorithms.CobylaOptimizer.__init__")(\[rhobeg, rhoend, maxfun, disp, …]) | Initializes the CobylaOptimizer. |
| [`get_compatibility_msg`](#qiskit.optimization.algorithms.CobylaOptimizer.get_compatibility_msg "qiskit.optimization.algorithms.CobylaOptimizer.get_compatibility_msg")(problem) | Checks whether a given problem can be solved with this optimizer. |
| [`is_compatible`](#qiskit.optimization.algorithms.CobylaOptimizer.is_compatible "qiskit.optimization.algorithms.CobylaOptimizer.is_compatible")(problem) | Checks whether a given problem can be solved with the optimizer implementing this method. |
| [`multi_start_solve`](#qiskit.optimization.algorithms.CobylaOptimizer.multi_start_solve "qiskit.optimization.algorithms.CobylaOptimizer.multi_start_solve")(minimize, problem) | Applies a multi start method given a local optimizer. |
| [`solve`](#qiskit.optimization.algorithms.CobylaOptimizer.solve "qiskit.optimization.algorithms.CobylaOptimizer.solve")(problem) | Tries to solves the given problem using the optimizer. |
## Attributes
| | |
| -------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------ |
| [`clip`](#qiskit.optimization.algorithms.CobylaOptimizer.clip "qiskit.optimization.algorithms.CobylaOptimizer.clip") | Returns the clip value for this optimizer. |
| [`trials`](#qiskit.optimization.algorithms.CobylaOptimizer.trials "qiskit.optimization.algorithms.CobylaOptimizer.trials") | Returns the number of trials for this optimizer. |
### clip
<Attribute id="qiskit.optimization.algorithms.CobylaOptimizer.clip">
Returns the clip value for this optimizer.
**Return type**
`float`
**Returns**
The clip value.
</Attribute>
### get\_compatibility\_msg
<Function id="qiskit.optimization.algorithms.CobylaOptimizer.get_compatibility_msg" signature="get_compatibility_msg(problem)">
Checks whether a given problem can be solved with this optimizer.
Checks whether the given problem is compatible, i.e., whether the problem contains only continuous variables, and otherwise, returns a message explaining the incompatibility.
**Parameters**
**problem** (`QuadraticProgram`) The optimization problem to check compatibility.
**Return type**
`str`
**Returns**
Returns a string describing the incompatibility.
</Function>
### is\_compatible
<Function id="qiskit.optimization.algorithms.CobylaOptimizer.is_compatible" signature="is_compatible(problem)">
Checks whether a given problem can be solved with the optimizer implementing this method.
**Parameters**
**problem** (`QuadraticProgram`) The optimization problem to check compatibility.
**Return type**
`bool`
**Returns**
Returns True if the problem is compatible, False otherwise.
</Function>
### multi\_start\_solve
<Function id="qiskit.optimization.algorithms.CobylaOptimizer.multi_start_solve" signature="multi_start_solve(minimize, problem)">
Applies a multi start method given a local optimizer.
**Parameters**
* **minimize** (`Callable`\[\[`ndarray`], `Tuple`\[`ndarray`, `Any`]]) A callable object that minimizes the problem specified
* **problem** (`QuadraticProgram`) A problem to solve
**Return type**
`OptimizationResult`
**Returns**
The result of the multi start algorithm applied to the problem.
</Function>
### solve
<Function id="qiskit.optimization.algorithms.CobylaOptimizer.solve" signature="solve(problem)">
Tries to solves the given problem using the optimizer.
Runs the optimizer to try to solve the optimization problem.
**Parameters**
**problem** (`QuadraticProgram`) The problem to be solved.
**Return type**
`OptimizationResult`
**Returns**
The result of the optimizer applied to the problem.
**Raises**
[**QiskitOptimizationError**](qiskit.optimization.QiskitOptimizationError "qiskit.optimization.QiskitOptimizationError") If the problem is incompatible with the optimizer.
</Function>
### trials
<Attribute id="qiskit.optimization.algorithms.CobylaOptimizer.trials">
Returns the number of trials for this optimizer.
**Return type**
`int`
**Returns**
The number of trials.
</Attribute>
</Class>