Генетический алгоритм

1function geneticAlgorithm(
2  popSize: number,
3  geneLen: number,
4  generations: number,
5  rng: () => number,
6) {
7  // фитнес: число единиц (цель — все единицы)
8  const fitness = (g: number[]) => g.reduce((s, b) => s + b, 0)
9 
10  let pop = Array.from({ length: popSize }, () =>
11    Array.from({ length: geneLen }, () => (rng() < 0.5 ? 0 : 1)))
12 
13  for (let gen = 0; gen < generations; gen++) {
14    pop.sort((a, b) => fitness(b) - fitness(a)) // отбор
15    const next: number[][] = []
16    while (next.length < popSize) {
17      const p1 = pop[tournament(pop, rng)]!
18      const p2 = pop[tournament(pop, rng)]!
19      const cut = Math.floor(rng() * geneLen)   // кроссовер
20      const child = [...p1.slice(0, cut), ...p2.slice(cut)]
21      const i = Math.floor(rng() * geneLen)     // мутация
22      child[i] ^= 1
23      next.push(child)
24    }
25    pop = next
26  }
27 
28  return pop.sort((a, b) => fitness(b) - fitness(a))[0]!
29}