Required: DEAP

This module contains functions for implementing an persistent NSGA2 generator function. The evaluation of the fitness of the current population’s members occurs in evaluate_pop, where the points are communicated to the libEnsemble manager; the manager coordinates their evaluation and then returns their fitness_values.

persistent_deap_nsga2.deap_nsga2(H, persis_info, gen_specs, libE_info)

An implementation of the NSGA2 evolutionary algorithm.

persistent_deap_nsga2.evaluate_pop(g, deap_object, Out, ps)

Evaluates the fitness of a population by communicating the individuals in the population to the libEnsemble manager, and then awaiting their fitness_values.


Returns a DEAP toolbox for use in a NSGA2 loop, derived from this example.