Description Usage Arguments Examples
For easier use with the IOHexperimenter
A genetic algorithm that controls the mutation rate (strength) using the so-called 2-rate self-adaptation mechanism: the mutation rate is based on a parameter r. For each generation, half offspring are generated by mutation rate 2r/dim, and half by r/2dim. r that the best offspring has been created with will be inherited by probability 3/4, the other by 1/4.
1 2 3 4 | IOH_two_rate_GA(IOHproblem, lambda_ = 1, budget = NULL)
two_rate_GA(dimension, obj_func, target_hit = function() { FALSE },
lambda_ = 2, budget = NULL, set_parameters = NULL)
|
IOHproblem |
An IOHproblem object |
lambda_ |
The size of the offspring |
budget |
How many times the objective function can be evaluated |
dimension |
Dimension of search space |
obj_func |
The evaluation function |
target_hit |
Optional, function which enables early stopping if a target value is reached |
set_parameters |
Function to call to store the value of the registered parameters |
1 |
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