class_docstr: A MFO class, inherited from Optimizer.
  
  This is the designed class to define MFO-related
  variables and methods.
  
  References:
      S. Mirjalili. Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm.
      Knowledge-Based Systems (2015).
docstr: Initialization method.
  
  Args:
      params: Contains key-value parameters to the meta-heuristics.
docstr_tok: ["Initialization","method",".","Args",":","params",":","Contains","key-value","parameters","to","the","meta-heuristics","."]
code: def __init__(self, params: Optional[Dict[str, Any]] = None) -> None:
      """Initialization method.
  
      Args:
          params: Contains key-value parameters to the meta-heuristics.
  
      """
  
      logger.info("Overriding class: Optimizer -> MFO.")
  
      super(MFO, self).__init__()
  
      self.b = 1
  
      self.build(params)
  
      logger.info("Class overrided.")
  
file_path: opytimizer/opytimizer/optimizers/swarm/mfo.py
imports: import copy
  from typing import Any, Dict, Optional
  import numpy
  import opytimizer.math.random
  import opytimizer.utils.exception
  from opytimizer.core import Optimizer
  from opytimizer.core.space import Space
  from opytimizer.utils import logging
label_desc: Use image node_id 1 to create a new MFO object from inherited base classes: Optimizer with example: obj = MFO(params)