class_docstr: A WCA class, inherited from Optimizer.
  
  This is the designed class to define WCA-related
  variables and methods.
  
  References:
      H. Eskandar.
      Water cycle algorithm – A novel metaheuristic optimization method for
      solving constrained engineering optimization problems.
      Computers & Structures (2012).
class_docstr_tok: ["A","WCA","class",",","inherited","from","Optimizer",".","This","is","the","designed","class","to","define","WCA-related","variables","and","methods",".","References",":","H.","Eskandar",".","Water","cycle","algorithm","\u2013","A","novel","metaheuristic","optimization","method","for","solving","constrained","engineering","optimization","problems",".","Computers","&","Structures","(","2012",")","."]
docstr: Maximum evaporation condition.
docstr_tok: ["Maximum","evaporation","condition","."]
code: def d_max(self) -> float:
      """Maximum evaporation condition."""
  
      return self._d_max
  
imports: from typing import Any, Dict, List, Optional
  import numpy
  import opytimizer.math.random
  import opytimizer.utils.exception
  from opytimizer.core import Optimizer
  from opytimizer.core.agent import Agent
  from opytimizer.core.function import Function
  from opytimizer.core.space import Space
  from opytimizer.utils import logging
label_desc: Use image node_id 4 for calling the WCA obj's underlying member method code with example usage: obj.d_max() and returns: self