artificial intelligence - Ranking Selection in Genetic Algorithm code

Question

I need code for the ranking selection method on a genetic algorithm. I have create roulette and tournament selections method but now I need ranking and I am stuck.

My roulette code is here (I am using atom struct for genetic atoms) :

const int roulette (const atom *f)
{
  int i;
  double sum, sumrnd;

  sum = 0;
  for (i = 0; i < N; i++)
    sum += f[i].fitness + OFFSET;

  sumrnd = rnd () * sum;

  sum = 0;
  for (i = 0; i < N; i++) {
    sum += f[i].fitness + OFFSET;
    if (sum > sumrnd)
      break;
  }

  return i;
}

Where atom :

typedef struct atom
{
  int geno[VARS];
  double pheno[VARS];
  double fitness;
} atom;

Answer 1

Rank selection is easy to implement when you already know on roulette wheel selection. Instead of using the fitness as probability for getting selected you use the rank. So for a population of N solutions the best solution gets rank N, the second best rank N-1, etc. The worst individual has rank 1. Now use the roulette wheel and start selecting.

The probability for the best individual to be selected is N/( (N * (N+1))/2 ) or roughly 2 / N, for the worst individual it is 2 / (N*(N+1)) or roughly 2 / N^2.

This is called linear rank selection, because the ranks form a linear progression. You can also think of ranks forming a geometric progression, such as e.g 1 / 2^n where n is ranging from 1 for the best individual to N for the worst. This of course gives much higher probability to the best individual.

You can look at the implementation of some selection methods in HeuristicLab.