class_docstr: An AEO class, inherited from Optimizer.
  
  This is the designed class to define AEO-related
  variables and methods.
  
  References:
      W. Zhao, L. Wang and Z. Zhang.
      Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm.
      Neural Computing and Applications (2019).
class_docstr_tok: ["An","AEO","class",",","inherited","from","Optimizer",".","This","is","the","designed","class","to","define","AEO-related","variables","and","methods",".","References",":","W.","Zhao",",","L.","Wang","and","Z.","Zhang",".","Artificial","ecosystem-based","optimization",":","a","novel","nature-inspired","meta-heuristic","algorithm",".","Neural","Computing","and","Applications","(","2019",")","."]
docstr: Performs the consumption update by an omnivore (eq. 8)
  
  Args:
      agent: Current agent.
      producer: Producer agent.
      consumer: Consumer agent.
      C: Consumption factor.
  
  Returns:
      (Agent): An updated consumption by an omnivore.
docstr_tok: ["Performs","the","consumption","update","by","an","omnivore","(","eq",".","8",")","Args",":","agent",":","Current","agent",".","producer",":","Producer","agent",".","consumer",":","Consumer","agent",".","C",":","Consumption","factor",".","Returns",":","(","Agent",")",":","An","updated","consumption","by","an","omnivore","."]
code: def _omnivore_consumption(
      self, agent: Agent, producer: Agent, consumer: Agent, C: float
  ) -> Agent:
      """Performs the consumption update by an omnivore (eq. 8)
  
      Args:
          agent: Current agent.
          producer: Producer agent.
          consumer: Consumer agent.
          C: Consumption factor.
  
      Returns:
          (Agent): An updated consumption by an omnivore.
  
      """
  
      a = copy.deepcopy(agent)
  
      r2 = r.generate_uniform_random_number()
      a.position += C * r2 * (a.position - producer.position) + (
          1 - r2
      ) * (a.position - consumer.position)
  
      return a
  
file_path: opytimizer/opytimizer/optimizers/population/aeo.py
imports: import copy
  from typing import Any, Dict, List, Optional
  import numpy
  import opytimizer.math.random
  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 AEO obj's underlying member method code with example usage: obj._omnivore_consumption(agent, producer, consumer, C) and returns: a