opytimizer.optimizers.evolutionary.rra

Runner-Root Algorithm.

class opytimizer.optimizers.evolutionary.rra.RRA(params: Optional[Dict[str, Any]] = None)

An RRA class, inherited from Optimizer.

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

References

F. Merrikh-Bayat. The runner-root algorithm: A metaheuristic for solving unimodal and multimodal optimization problems inspired by runners and roots of plants in nature. Applied Soft Computing (2015).

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

Initialization method.

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

Length of runners.

d_root

Length of roots.

tol

Cost function tolerance.

max_stall

Maximum number of stalls.

n_stall

Current number of stalls.

last_best_fit

Previous best fitness value.

Performs the stalling random larrge or small search (eq. 4 and 5).

Parameters:
  • daughters – Daughters.
  • function – A Function object that will be used as the objective function.
  • is_large – Whether to perform the large or small search.
_roulette_selection(fitness: List[float], a: Optional[float] = 0.1) → int

Performs a roulette selection on the population (eq. 8).

Parameters:
  • fitness – A fitness list of every agent.
  • a – Selection regularizer.
Returns:

The selected index of the population.
Return type:

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

Wraps Runner-Root Algorithm 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.