code: def main():
      random.seed(64)
  
      MU, LAMBDA = 50, 100
      pop = toolbox.population(n=MU)
      hof = tools.ParetoFront()
      stats = tools.Statistics(lambda ind: ind.fitness.values)
      stats.register("avg", numpy.mean, axis=0)
      stats.register("std", numpy.std, axis=0)
      stats.register("min", numpy.min, axis=0)
      stats.register("max", numpy.max, axis=0)
  
      algorithms.eaMuPlusLambda(
          pop,
          toolbox,
          mu=MU,
          lambda_=LAMBDA,
          cxpb=0.5,
          mutpb=0.2,
          ngen=150,
          stats=stats,
          halloffame=hof,
      )
  
      return pop, stats, hof
  
file_path: deap/examples/ga/kursawefct.py
imports: import array
  import logging
  import random
  import numpy
  from deap import algorithms
  from deap import base
  from deap import benchmarks
  from deap import creator
  from deap import tools
label_desc: Use image node_id 2 for calling a global function with example usage: main() and returns: pop,  stats,  hof