opytimizer.optimizers.population.rfo

Red Fox Optimization.

class opytimizer.optimizers.population.rfo.RFO(params: Optional[Dict[str, Any]] = None)

A RFO class, inherited from Optimizer.

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

References

D. Polap and M. Woźniak. Red fox optimization algorithm. Expert Systems with Applications (2021).

__init__(params: Optional[Dict[str, Any]] = None) → None

Initialization method.

Parameters:params – Contains key-value parameters to the meta-heuristics.

phi

Observation angle.

theta

Weather condition.

p_replacement

Percentual of foxes replacement.

n_replacement

Number of foxes to be replaced.

compile(space: opytimizer.core.space.Space) → None

Compiles additional information that is used by this optimizer.

Parameters:space – A Space object containing meta-information.

_rellocation(agent: opytimizer.core.agent.Agent, best_agent: opytimizer.core.agent.Agent, function: opytimizer.core.function.Function) → None

Performs the fox rellocation procedure.

Parameters:

• agent – Current agent.
• best_agent – Best agent.
• function – A Function object that will be used as the objective function.

_noticing(agent: opytimizer.core.agent.Agent, function: opytimizer.core.function.Function, alpha: float) → None

Performs the fox noticing procedure.

Parameters:

• agent – Current agent.
• function – A Function object that will be used as the objective function.
• alpha – Scaling parameter.

update(space: opytimizer.core.space.Space, function: opytimizer.core.function.Function) → None

Wraps Red Fox Optimization over all agents and variables.

Parameters:

• space – Space containing agents and update-related information.
• function – A Function object that will be used as the objective function.