genetic | Examples about genetic algorithms for parallel computing | Machine Learning library

While this is not a regex solution, this certainly works:

This happens because writing to a file is an expensive operation, so python actually writes to a buffer. When the buffer fills up (it's slightly more complicated than that), or when the file handle is closed, the buffer is flushed to the filesystem.

In your case, this is what that looks like:

You should read https://www.jstatsoft.org/article/view/v053i04. You don't have permutation problem but selection one hence you should use binary type of genetic algorithm. Because you want to select exclusively 10 (10 ones and 990 zeroes) you should probably write your own genetic operators because that is constraint that will hardly ever be satisfied by default operators (with inclusion of -Inf in fitness function if you have more than 10 zeroes). One approach:

Population (k tells how much ones you want):

You can define a recursive function f (see it within function thomas2), which can be any number of rows k (1 <= k <= nrow(mat))

My comments turned into an answer:

So it looks like you need to run couples_selection() on the population for each generation, then run get_offspring() on the couples returned from couples_selection(), and then run eval_pop() on the population returned from get_offspring(). Then, the winner of that generation will be the individual from the returned list of eval_pop() that had the highest score. It looks like eval_pop() is supposed to sort its returned list in descending order of score, but doesn't appear to; otherwise, the [0] index of the returned list would be the one with the highest score, aka the winner.

Also, if you're returning sorted_pop_with_score[0] as the absolute winner, then it seems like you need to be adding the winner of each generation to some list, and then run eval_pop() on that list after you complete all the generations, and set sorted_pop_with_score to the result of that final eval_pop().

It could also contain a less fit solution too, to escape a local optima. That's why the global best solution must be remembered too, unless the first individual is guaranteed to contain it and survive.

Start by checking what you have.

for (int j = 0; j < nTh; i++)

You are increasing i instead of j and therefor are stuck in an infinite loop.