Parallel Genetic Algorithm with scala

Create for personal use (train my bots on codingame.com and another competitions)

my goal was to create easy to use and performance solution

(as evaluating function can be complex, so it's important to make less evaluation of fitness function as possible) current solution linearly scale with CPU cores

with small data and simple fitness function performance usual don't have any matter also performance for parallel algorithm can be even worse

but than data is growing and fitness function is become really complex (for example fitness function relaying on game simulation result) there parallel working is huge, also less amount of fitness evaluation is important

using

to make use GeneticAlgoritm just use

     GeneticAlgorithm(geneBase, geneSize, fitness, mutationRate)

• geneBase - baze whitch is used to generate Genes
• geneSize - numbers element of resulting Gene
• fitness - your evaluating function from input DNA to Double
• mutationRate - percent of random mutation (from 1 to 100) [optional]

see sample in AlgoTest

correctness testing

use sbt testOnly Algotest

usual string permutation and similarity evaluation to check correctness

performance evaluating

I increase working time of fitness function with dummy operation like sleep (only in tests) in order to optimise solution to real workflow

use sbt testOnly Performance