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See the recommended documentation of this function
crossover_ga_binary
A crossover function for binary code
Syntax
[Crossed_Indiv1, Crossed_Indiv2, mix] = crossover_ga_binary(Indiv1, Indiv2, param)
Arguments
- Indiv1
A string
the first individual (here a binary code) to be crossed-over.
- Indiv2
A string
the second individual to be crossed-over.
- param
a list of parameters.
"binary_length"
: an integer, the length of the binary code (default 8)."multi_cross"
: a boolean. If%T
then we allow several cuts in the binary code (default%F
)."multi_cross_nb"
: an integer, the number of cuts in the binary code. Only used when multi_cross is set to %T (default 2).
- Crossed_Indiv1
A string
The first individual obtained by the cross-over function.
- Crossed_Indiv2
A string
The second individual obtained by the cross-over function.
- mix
A vector of integers
The positions the crossover occurred.
Description
This function implements a classical binary cross-over.
crossover_ga_binary(Indiv1, Indiv2)
generates
the crossover between Indiv1
and Indiv2
by merging the characters from each string.
A position i
is chosen randomly
between 1 and the length of the binary code.
Then Indiv1
and Indiv2
are split in two parts:
the first i
characters (the head),
and the remaining characters (the tail).
The crossover swaps the tails of the binary codes.
The following schema presents the crossover:
Indiv1=[H1 T1] Indiv2=[H2 T2] Crossed_Indiv1=[H1 T2] Crossed_Indiv2=[H2 T1]
The behaviour of the function can be modified with the use of param
:
- binary_length
changes the minimal length of the binary code, by default 8 characters.
Binary code for
Indiv1
orIndiv2
of lower length are zero padded to the right to be ofbinary_length
length ormax([length(Indiv1), length(Indiv2)])
whichever is greater.- multi_cross
if set to
%T
multiple crossovers can happen (default%F
)- multi_cross_nb
the number of locations for crossovers. (default 2 if multi_cross is set to
%T
, 1 otherwise)
Random number generator
crossover_ga_binary
is based
on grand
for generating the random samples.
Use grand("setsd", seed)
to change the seed
for crossover_ga_binary
.
Examples
A = "11100000" B = "00011111" [A_crossed, B_crossed, mix] = crossover_ga_binary(A, B) C = dec2bin(2^16 - 1, 16) D = "0" param = init_param(); param = add_param(param, "binary_length", 16); // Code of length 16 param = add_param(param, "multi_cross", %T); // Multiple Crossover param = add_param(param, "multi_cross_nb", 3); // Occurs over 3 locations [C_crossed, D_crossed, mix] = crossover_ga_binary(C, D, param)
See also
- crossover_ga_binary — A crossover function for binary code
- crossover_ga_default — A crossover function for continuous variable functions
- mutation_ga_binary — A function which performs binary mutation
- optim_ga — A flexible genetic algorithm
- grand — Random numbers
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