title: Adaptive mutation/crossover rates for genetic algorithms
body: <p>I've been looking into ways I can implement an adaptive mutation rate for a genetic algorithm I'm working on. I've seen an algorithm which uses the current individuals fitness and the average population fitness to calculate a mutation rate, however I'm not sure it's very effective.</p>
  
  <p>In the algorithm I've seen you do the following:</p>
  
  <pre><code>mutationRate = (bestFitness - individualFitness) / (bestFitness - averageFitness) * 0.5
  </code></pre>
  
  <p>Would this be a good approach or are there better?</p>