In OpenMOLE evolutionary algorithms you can suggest genomes to start with. You can suggest genomes using an OMR file, a CSV file or setting it manually. It might be a way to inject use the results found a previous run to bootstrap a new one.
In the following examples we demonstrate suggestion using NSGA2, but it works with any evolutionary method.

From an OMR file 🔗

If you saved the results of an evolution in a file called previous_result.omr, you can start an evolution using these results using suggestion. The file must contain values for each parts of the genome.

val i1 = Val[Double]
val i2 = Val[Double]

val fitness = Val[Double]

val rastrigin = ScalaTask("""
  val i = Vector(i1, i2)
  val fitness = 10 * i.size + i.map(x => (x * x) - 10 * math.cos(2 * Pi * x)).sum
  """) set (
    inputs += (i1, i2),
    outputs += fitness
  )


NSGA2Evolution(
  evaluation = rastrigin,
  objective = fitness,
  genome = Seq(
    i1 in (-5.12 to 5.12),
    i2 in (-5.12 to 5.12)
  ),
  termination = 100,
  parallelism = 10,
  suggestion = workDirectory / "previous_result.omr"
) hook (workDirectory / "result.omr")

From an CSV file 🔗

You can also suggest genome values using a CSV file. The file must contain values for each parts of the genome, for instance:

i1,i2
-1.79,-0.95
-2.79,-0.10

You can suggest the genome listed in this file as follows:

val i1 = Val[Double]
val i2 = Val[Double]

val fitness = Val[Double]

val rastrigin = ScalaTask("""
  val i = Vector(i1, i2)
  val fitness = 10 * i.size + i.map(x => (x * x) - 10 * math.cos(2 * Pi * x)).sum
  """) set (
    inputs += (i1, i2),
    outputs += fitness
  )


NSGA2Evolution(
  evaluation = rastrigin,
  objective = fitness,
  genome = Seq(
    i1 in (-5.12 to 5.12),
    i2 in (-5.12 to 5.12)
  ),
  termination = 100,
  parallelism = 10,
  suggestion = workDirectory / "suggestion.csv"
) hook (workDirectory / "result.omr")

Suggest in the script 🔗

You can also suggest initial genomes in the script, using the following syntax:

val i1 = Val[Double]
val i2 = Val[Double]

val fitness = Val[Double]

val rastrigin = ScalaTask("""
  val i = Vector(i1, i2)
  val fitness = 10 * i.size + i.map(x => (x * x) - 10 * math.cos(2 * Pi * x)).sum
  """) set (
    inputs += (i1, i2),
    outputs += fitness
  )


NSGA2Evolution(
  evaluation = rastrigin,
  objective = fitness,
  genome = Seq(
    i1 in (-5.12 to 5.12),
    i2 in (-5.12 to 5.12)
  ),
  termination = 100,
  parallelism = 10,
  suggestion = Seq(
    Suggestion(i1 := 1.4, i2 := 1.3),
    Suggestion(i1 := -1.3, i2 := -1.2)
  )
) hook (workDirectory / "file.omr")