Comments (3)
It is just default selection
and crossover
functions are incorrect. Try some other functions. BTW, binary chromosomes supported as Vector{Bool}
. I'll write some examples. Thanks for bringing this issue.
from evolutionary.jl.
If you call your example as follows:
julia> ga(fitness, 7, selection=((x,n)->1:n))
([0.984655,0.684742,0.49106,0.204153,0.26621,0.660357,0.42944],13.804710257390415,700,0.0)
If you want binary chromosomes use Vector{Bool}
to initialize the population (BitVector
isn't supported}:
julia> ga(fitness, 7, selection=((x,n)->1:n), initPopulation = collect(randbool(7)))
(Bool[false,true,false,true,true,false,false],10,700,0)
from evolutionary.jl.
Thank you, that sorted out the problem perfectly!
from evolutionary.jl.
Related Issues (20)
- Defining intitial value for parameters as a vector for each parameter HOT 1
- "maximization context"? HOT 2
- Zero-index bug in recombination operators that use `inmap` HOT 1
- Cannot modify trace HOT 3
- Default for `recombination` in `ES` causes error due to `rng` kwarg
- GA returns most recent (rather than best) value? HOT 6
- DE returns most recent population info, rather than the minimizer HOT 2
- Function with binary and real inputs HOT 1
- ES selection strategies HOT 3
- differential evolution does not honour the parallelization option HOT 1
- Access the population during GA evolution HOT 1
- Crossover functions not working as intended for integer sequences?
- Not being able to parallelize.
- nsga2 use of StackViews only allows concrete types
- MILX Operator not working with integer solutions
- Symbolic regression examples not working in version 0.11.1 HOT 1
- Cannot get examples MLP to work HOT 3
- DE rastrigin tests sometimes randomly fail
- Default `GA` and `DE` don't seem to work in v0.11.1 HOT 6
- Integer Problem with MILX and MIPM HOT 11
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from evolutionary.jl.