randomkeyga.scala

Random Key Genetic Algorithms for Permutation Optimization in Scala

Example

Traveling Salesman Example

import org.expr.tsp._
@main def hello(): Unit =
  

  val distanceMatrix = List(
      List(0, 1, 2, 3, 4.0),
      List(1, 0, 1, 2, 3.0),
      List(2, 1, 0, 1, 2.0),
      List(3, 2, 1, 0, 1.0),
      List(4, 3, 2, 1, 0.0)
    )

  val popsize = 100
  val crossoverprob = 0.9
  val mutationprob = 0.1
  val elitism = 1
  val maxiter = 100

  val tspresult = tsp(distanceMatrix, 
                    popsize, 
                    crossoverprob, 
                    mutationprob, 
                    elitism, 
                    maxiter)

  val route = tspresult.route
  val cost = tspresult.cost
  Console.println(Console.YELLOW + "The Random Key Genetic Algorithm - Example")
  Console.println(Console.RED + "===========================================")
  Console.println(Console.GREEN + "Distance Matrix:")
  distanceMatrix.foreach(row => Console.println(Console.MAGENTA + row.mkString(" ")))
  Console.println(Console.GREEN + s"Route: $route")
  Console.println(Console.GREEN + s"Cost: $cost")

The output is

#> sbt run
sbt:rkga> run
[info] running hello 
The Random Key Genetic Algorithm - Example
===========================================
Distance Matrix:
0.0 1.0 2.0 3.0 4.0
1.0 0.0 1.0 2.0 3.0
2.0 1.0 0.0 1.0 2.0
3.0 2.0 1.0 0.0 1.0
4.0 3.0 2.0 1.0 0.0
Route: List(0, 4, 3, 2, 1)
Cost: 8.0
[success] Total time: 0 s, completed Sep 26, 2024, 10:42:12 PM