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CE

Module: opytimizer.optimizers.single_objective.evolutionary.ce

A CE class, inherited from Optimizer.

This is the designed class to define CE-related variables and methods.

References: Pei, Y. (2020, October). Chaotic evolution algorithm with elite strategy in single-objective and multi-objective optimization. In 2020 IEEE international conference on systems, man, and cybernetics (SMC) (pp. 579-584). IEEE.

Constructor​

CE(params: Optional[Dict[str, Any]] = None, DR: float = 0.7, CR: float = 0.7, p: Tuple[float, float] = (0.02, 0.1), jump: int = 10, chaotic_system: Literal['logistic', 'gauss', 'tent', 'henon'] = 'tent')

Parameters​

ParameterTypeDefaultDescription
paramsOptional[Dict[str, Any]]None—
DRfloat0.7—
CRfloat0.7—
pTuple[float, float](0.02, 0.1)—
jumpint10—
chaotic_systemLiteral['logistic', 'gauss', 'tent', 'henon']'tent'—

Methods​

compile​

compile(self, space)

Compiles additional information that is used by this optimizer.

This method is called before the optimization procedure and makes sure that the additional variable is available as a property.

Parameters​

ParameterTypeDefaultDescription
space—

evaluate​

evaluate(self, space, function)

Evaluates the search space according to the objective function.

If you need a specific evaluate method, please re-implement it on child's class.

Also, note that function only accept arguments that are found on Opytimizer class.

Parameters​

ParameterTypeDefaultDescription
spaceA Space object that will be evaluated.
functionA Function object serving as an objective function.

update​

update(self, space: opytimizer.core.space._SingleObjectiveSpace, function: opytimizer.core.function.Function)

Updates the agents' position array.

As each child has a different procedure of update, you will need to implement it directly on its class.

Parameters​

ParameterTypeDefaultDescription
spaceopytimizer.core.space._SingleObjectiveSpace—
functionopytimizer.core.function.Function—