Grey Wolf Optimizer.

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

A GWO class, inherited from Optimizer.

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


S. Mirjalili, S. Mirjalili and A. Lewis. Grey Wolf Optimizer. Advances in Engineering Software (2014).

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

Initialization method.

Parameters:params – Contains key-value parameters to the meta-heuristics.
_calculate_coefficients(a: float) → Tuple[float, float]

Calculates the mathematical coefficients.

Parameters:a – Linear constant.
Returns:Both A and C coefficients.
Return type:(Tuple[float, float])
update(space: opytimizer.core.space.Space, function: opytimizer.core.function.Function, iteration: int, n_iterations: int) → None

Wraps Grey Wolf Optimization over all agents and variables.

  • space – Space containing agents and update-related information.
  • function – A Function object that will be used as the objective function.
  • iteration – Current iteration.
  • n_iterations – Maximum number of iterations.