Instance-evolving EA.

To be written ...

evoprob(
  n,
  P,
  maximize = FALSE,
  runner.fun,
  fitness.fun,
  mut.fun,
  diversity.fun = NULL,
  max.iters = 10L,
  max.time = Inf,
  logger = NULL,
  ...
)

Arguments

n	[integer(1L)] Desired instance size.
P	[list] Initial population. This is problem dependent. Therefore, the used must provide it.
maximize	[logical(1)] Is the goal to maximize performance values? Defaults to FALSE.
runner.fun	[function] Function used to run algorithms on problem instance. Should return aggregated performance values.
fitness.fun	[function] Fitness function.
mut.fun	[function] Mutation operator.
diversity.fun	[function] Diversity function, i.e. function that calculates the diversity of a set of instances.
max.iters	[integer(1)] Stopping condition: maximum number of iterations.
max.time	[integer(1)] Maximum time in seconds. Default is NULL, i.e. the number of iterations serves as the single termination criterion.
logger	[evoprob_logger] Optional logger environemt (see init_logger). Possible values for parameter what are iter = "numeric" Mandatory iteration counter. time = "numeric" Time passed in seconds. P = "list" The population. fP = "list" The fitness values. div = "numeric" Scalar diversity measure. divtab = "list" Vector of absolute frequencies of algorithm rankings. Default is NULL, i.e., logging is not active.
...	[any] Not used at the moment.

Value

[list]