title: Resuming an optimization with pyevolve
body: <p>I have done an optimization with Pyevolve and after a look at the results I wanted to add a few generation to have a better convergence. As an evaluation is quite long, I was wondering if I can resume my optimization to the last generation and add like 20 more generations. Everything must be set in the DB I hope so he can be possible.</p>
  
  <p>Here is my GA properties (similar to the first example but with a more complicated evaluation function):</p>
  
  <pre><code>    # Genome instance, 1D List of 6 elements
  genome = G1DList.G1DList(6)
  
  # Sets the range max and min of the 1D List
  genome.setParams(rangemin=1, rangemax=15)
  
  # The evaluator function (evaluation function)
  genome.evaluator.set(eval_func)
  
  # Genetic Algorithm Instance
  ga=GSimpleGA.GSimpleGA(genome)
  
  # Set the Roulette Wheel selector method, the number of generations and
  # the termination criteria
  ga.selector.set(Selectors.GRouletteWheel)
  ga.setGenerations(50)
  ga.setPopulationSize(10)
  ga.terminationCriteria.set(GSimpleGA.ConvergenceCriteria)
  
  # Sets the DB Adapter, the resetDB flag will make the Adapter recreate
  # the database and erase all data every run, you should use this flag
  # just in the first time, after the pyevolve.db was created, you can
  # omit it.
  sqlite_adapter = DBAdapters.DBSQLite(identify="F-Beam-Optimization", resetDB=True)
  ga.setDBAdapter(sqlite_adapter)
  
  # Do the evolution, with stats dump
  # frequency of 5 generations
  ga.evolve(freq_stats=2)
  </code></pre>
  
  <p>Anyone with the idea?</p>