setupECRControl(n.population, n.offspring, n.mating.pool = floor(n.population/2), representation, survival.strategy = "plus", n.elite = 0L, monitor = setupConsoleMonitor(), stopping.conditions = list(), logger = NULL, custom.constants = list(), vectorized.evaluation = FALSE)integer(1)]
Number of individuals in the population.integer(1)]
Number of individuals generated in each generation.integer(1)]
Number of individuals which can potentially participate in the
generation of offspring.
Default is half of the population size.character(1)]
Genotype representation of the parameters. Available are “binary”,
“float”, “permutation” and “custom”.character(1)]
Determines the survival strategy used by the EA. Possible are “plus” for
a classical (mu + lambda) strategy and “comma” for (mu, lambda).
Default is “plus”.integer(1)]
Number of fittest individuals of the current generation that shall be copied to the
next generation without changing. Keep in mind, that the algorithm
does not care about this option if the survival.strategy is set to 'plus'.
Default is 0.function]
Monitoring function.
Default is NULL, i.e. no monitoring.list]
List of functions of type ecr_terminator. At least one stopping
condition needs to be passed.
Default is the empty list.function]
Monitoring object used to log stuff.
Default is NULL which means no logging at all.
See setupOptPathLoggingMonitor for ecr's build-in logger.list]
Additional constants which should be available to all generators and operators.
Defaults to empty list.logical(1L)]
Is the fitness/objective function vectorized? I.e., does the fitness function accept
a list? This allows for faster execution or parallelization by hand.
If TRUE the following destinction on the type of the objective function is made:
Default is FALSE.
ecr_control.