class_docstr: Optimises multiple objectives with random evaluations. 
docstr: Any set up specific to the method for multi-objective optimisation. 
docstr_tok: ["Any","set","up","specific","to","the","method","for","multi-objective","optimisation","."]
code: def _multi_opt_method_set_up(self):
      """Any set up specific to the method for multi-objective optimisation."""
      pass
  
imports: from argparse import Namespace
  import numpy
  from .random_optimiser import random_sample_from_cp_domain_wrapper
  from ..exd.cp_domain_utils import get_processed_func_from_raw_func_for_cp_domain, load_cp_domain_from_config_file
  from ..exd import domains
  from ..exd.exd_utils import get_euclidean_initial_qinfos, get_cp_domain_initial_qinfos
  from ..exd.experiment_caller import CPMultiFunctionCaller
  from .multiobjective_optimiser import MultiObjectiveOptimiser, multiobjective_opt_args
  from ..utils.option_handler import load_options
  from ..utils.reporters import get_reporter
  from ..utils.general_utils import map_to_bounds
label_desc: Use image node_id 2 for calling the RandomMultiObjectiveOptimiser obj's underlying member method code with example usage: obj._multi_opt_method_set_up() without return types