Genetic Algorithms in Elixir/

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Understanding Reinsertion

Understanding Reinsertion

Learn about reinsertion and the initialization required for its implementation.

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What is reinsertion?

Reinsertion is the process of taking chromosomes produced from selection, crossover, and mutation and then inserting them back into a population to move on to the next generation. Look at evolve/4 in genetic.ex. here:

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def evolve(population, problem, generation, opts \\ []) do
  population = evaluate(population, &problem.fitness_function/1, opts)
  best = hd(population)
  IO.write("\rCurrent best: #{best.fitness}\tGeneration: #{generation}")
  if problem.terminate?(population, generation) do
    best
  else
    {parents, leftover} = select(population, opts)
    children = crossover(parents, opts)
    children ++ leftover
    |> mutation(opts)
    |> evolve(problem, generation+1, opts)
  end
end

Recall from the lesson Customizing Selection in Your Framework, that combined children and leftover and mutated the result to form a new population. ...