gen.js

const POPULATION_SIZE = 100

class GeneticAlgorithm {
  generate(length) {
    let chromosome = ''
    
    for (let i = 0; i < length; i += 1) {
      chromosome += String(Number(Math.random(1) > 0.5))
    }
    
    return chromosome
  }
  
  static mutationsMap = {
    '0': '1',
    '1': '0',
  }
  
  mutate(chromosome, p) {
    let newChromosome = ''
    
    for (let bit of chromosome) {
      const willMutate = (Math.random() < p)
      if (willMutate) {
        bit = GeneticAlgorithm.mutationsMap[bit]
      }
      
      newChromosome += bit
    }
    
    return newChromosome
  }
  
  crossover(chromosome1, chromosome2, changeFrom) {
    let newChromosome1 = ''
    let newChromosome2 = ''
    
    for (const index in chromosome1) {
      let char1 = chromosome1[Number(index)]
      let char2 = chromosome2[Number(index)]
      
      if (index >= changeFrom) {
        [char1, char2] = [char2, char1]
      }
      
      newChromosome1 += char1
      newChromosome2 += char2
    }
    
    return [newChromosome1, newChromosome2]
  }
  
  select(population, fitnesses) {
    let fullFitness = fitnesses.reduce((sum, current) => sum + current)
    let selectedPoint = Math.random() * fullFitness
    let selectedChromosome = 0
    
    while (selectedPoint > 0) {
      selectedPoint -= fitnesses[selectedChromosome]
      selectedChromosome += 1
    }
    
    return population[selectedChromosome - 1]
  }
  
  run(fitness, length, p_c, p_m, iterations) {
    let population = []
    
    for (let i = 0; i < POPULATION_SIZE; i += 1) {
      population.push(this.generate(length))
    }
    
    let fitnesses = population.map(fitness)
    
    do {
      let newPopulation = []
      
      while (newPopulation.length < POPULATION_SIZE) {
        let chromosome1 = this.select(population, fitnesses)
        let chromosome2
        
        do {
          chromosome2 = this.select(population, fitnesses)
        } while (chromosome1 === chromosome2)
        
        const willCrossover = (Math.random() < p_c)
        if (willCrossover) {
          const crossoverPosition = Math.trunc(Math.random() * length)
          let [newChromosome1, newChromosome2] = this.crossover(chromosome1, chromosome2, crossoverPosition)
          
          newChromosome1 = this.mutate(newChromosome1, p_m)
          newChromosome2 = this.mutate(newChromosome2, p_m)
          
          newPopulation.push(newChromosome1, newChromosome2)
        }
      }
        
      population = newPopulation
      fitnesses = population.map(fitness)
    } while (!fitnesses.some(f => f === 1))
  
    for (let i = 0; i < POPULATION_SIZE; i += 1) {
      if (fitnesses[i] === 1) {
        return population[i]
      }
    }
  } 
}