onePlusOneGA: Simple (1 + 1) Genetic Algorithm.
Description
The simplest evolutionary algorithm one can imagine, namely the (1+1) EA/GA.
Maintains a population of a single individual x and uses just bitplip mutation
to generate a child y (obviously no recombination takes place), i.e., each gene
of x is flipped with probability p
independently. The best individual
survives.
This algorithm is of particular interest in the theory of evolutionary algorithms
and its performance is well understood for different function families.
A lot of interesting results exist.
Usage
onePlusOneGA(task, p = NULL, max.iter = NULL, max.evals = NULL, max.time = NULL, ...)
Arguments
task
[ecr_optimization_task
]
Optimization task. If a smoof_function
is passed it is automatically
converted into a task.
p
[numeric(1)
]
Mutation probability for bitplip mutation.
Default is $1/n$ where n is the length of the gene.
max.iter
[integer(1)
]
Maximal number of iterations. Default ist 100L
.
max.evals
[integer(1)
]
Maximal number of iterations/generations. Default is Inf
.
max.time
[integer(1)
]
Time budget in seconds. Default ist Inf
.
Value
[ecr_single_objective_result
]