class_docstr: A WAOA class, inherited from Optimizer.
  
  This is the designed class to define WAOA-related
  variables and methods.
  
  References:
      P. Trojovský and M. Dehghani. A new bio-inspired metaheuristic algorithm for
      solving optimization problems based on walruses behavior. Scientific Reports (2023).
docstr: Initialization method.
  
  Args:
      params (str): Contains key-value parameters to the meta-heuristics.
docstr_tok: ["Initialization","method",".","Args",":","params","(","str",")",":","Contains","key-value","parameters","to","the","meta-heuristics","."]
code: def __init__(self, params: Optional[Dict[str, Any]] = None) -> None:
      """Initialization method.
  
      Args:
          params (str): Contains key-value parameters to the meta-heuristics.
      """
  
      logger.info("Overriding class: Optimizer -> WAOA")
  
      super(WAOA, self).__init__()
  
      self.build(params)
  
      logger.info("Class overrided.")
  
file_path: opytimizer/opytimizer/optimizers/swarm/waoa.py
imports: import copy
  import time
  from typing import Any, Dict, Optional
  import numpy
  import opytimizer.math.random
  import opytimizer.utils.logging
  from opytimizer.core.function import Function
  from opytimizer.core.optimizer import Optimizer
  from opytimizer.core.space import Space
label_desc: Use image node_id 1 to create a new WAOA object from inherited base classes: Optimizer with example: obj = WAOA(params)