title: NSGA-2 multi-objective genetic algorithm. Anyone could give me a "simple explanation"?
body: <p>I'm working on a genetic algorithm.</p>
  
  <p>There are two objective and each one has its own fitness values (fv1,fv2).</p>
  
  <p>I know how generational(SGE) and steady-state(SS) genetic algorithms works.</p>
  
  <p>I'm trying to understand how NSGA-2 and SPEA-2 (I'm using the implementation of the java library JCLEC) work, particularly:</p>
  
  <ul>
  <li>what is the "external population" and how should it be sized</li>
  <li>what's the difference with  SS and SGE one-objective algorithm (a part from the fact each individual has just one fitness value)</li>
  </ul>
  
  <p>In case anyone is working with JCLEC library these are the parameters I setup:</p>
  
  <ul>
  <li>external population: 1000</li>
  <li>k-value: 10</li>
  <li>other attributes are the same of SS and SGE (population-size:100 , crossover: MPX crossover etc..)</li>
  </ul>