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Selection
The selection process is a key step in Evolutionary Algorithms. Selection drives the search process towards specific areas of the search space. The selection process operates on a population of individuals, and produces a population of "parents". These parents are then traditionally used by variation operators.
The linear genome mapping process in Grammatical Evolution can generate "invalid" individuals. Only valid individuals are selected by default in PonyGE2, however this can be changed with the argument:
--invalid_selection
or by setting the parameter INVALID_SELECTION to True in either a parameters file or in the params dictionary.
Tournament selection selects TOURNAMENT_SIZE individuals from the overall population, sorts them, and then returns the single individual with the best fitness. Since no individuals are removed from the original population, it is possible that the same individuals may be selected multiple times to appear in multiple tournaments, although the same individual may not appear multiple times in the same tournament.
Activate with:
--selection tournament
or by setting the parameter SELECTION to tournament in either a parameters file or in the params dictionary.
Tournament size is set by default at 2. This value can be changed with the argument:
--tournament_size [INT]
or by setting the parameter TOURNAMENT_SIZE to [INT] in either a parameters file or in the params dictionary, where [INT] is an integer which specifies the tournament size.
Truncation selection takes an entire population, sorts it, and returns the best SELECTION_PROPORTION of that population.
Activate with:
--selection truncation
or by setting the parameter SELECTION to truncation in either a parameters file or in the params dictionary.
Selection proportion is set by default at 0.5 (i.e. return the top 50% of the population). This value can be changed with the argument:
--selection_proportion [NUM]
or by setting the parameter SELECTION_PROPORTION to [NUM] in either a parameters file or in the params dictionary, where [NUM] is a float between 0 and 1.
NOTE that unless the specified SELECTION_PROPORTION is 1.0 (i.e. 100%), truncation selection necessarily returns a selected parent population that is smaller in size than the original population.
NSGA2 selection performs a pareto tournament selection on TOURNAMENT_SIZE individuals. Pareto selection takes into account both the pareto front of the individuals (to check for dominance) and the crowding comparison of the individuals (to ensure dispersion on the fronts). For more details on the NSGA-II operator see [Deb et al., 2002].
Activate with:
--selection nsga2_selection
or by setting the parameter SELECTION to nsga2_selection in either a parameters file or in the params dictionary.
NOTE that NSGA2 selection can only be used in conjunction with multiple objective optimisation problems.
NOTE that multi-objective optimisation compatible operators require a multi_objective = True attribute.