Simple but powerful Genetic Algorithm

Genetic.js

/**
 * Author: Matthias Krijgsman
 *
 * Genetic Operator: One-point crossover
 *
 * Options input json:
 *  size        - Population Size
 *  elimination - Elimination Rate
 *  mutation    - Mutation Rate
 *  geneSize    - DNA Size
 *
 * Methods:
 *  generate() - Generates a random list of dna
 *  next(x) - Takes x to the next generation
 *
 *  x input:
 *  json array
 *
 *  [
 *      {
 *          id: 0,
 *          score: 0,
 *          dna: "01001010"
 *      },
 *      {
 *          id: 1,
 *          score: 0,
 *          dna: "01001010"
 *      }
 *  ]
 *
 **/

var genetic;

String.prototype.setCharAt = function(index,chr) {
    if(index > this.length-1) return str;
    return this.substr(0,index) + chr + this.substr(index+1);
};

genetic = function(options){
    this.s = options.size;
    this.e = options.elimination;
    this.m = options.mutation;
    this.g = options.geneSize;
};

genetic.prototype.generate = function(){
    var result = [];
    for(var i = 0; i < this.s; i++){
        var dna = "";
        for(var n = 0; n < this.g; n++){
            dna += Math.round(Math.random());
        }
        result.push(dna);
    }
    return result;
};

genetic.prototype.next = function(data){
    data.sort(function(a,b){return b.score - a.score});
    var i = Math.round(this.s*this.e);
    if(i%2){i--}
    var p = this.choose(i);

    var d = [];

    for(var i in p){
        var p1 = p[i][0];
        var p2 = p[i][1];
        var r = this.operator(data[p1].dna, data[p2].dna);
        d.push(r[0]);
        d.push(r[1]);
    }

    for(var i in d){
        data[((this.s-1)-i)].dna = d[i];
    }
    data.sort(function(a,b){return a.id - b.id});

    for(var i in data){
        if(Math.random() < this.m){
            var x = Math.floor(Math.random() * this.g);
            if(data[i].dna[x] == "0"){
                data[i].dna = data[i].dna.setCharAt(x, "1");
            }else{
                data[i].dna = data[i].dna.setCharAt(x, "0");
            }
        }
    }

    return data;
};

genetic.prototype.choose = function(x){
    var r = [];
    var x2 = x/2;
    while(x2--){
        var p1 = Math.round(Math.random() * (this.s-x));
        var p2 = Math.round(Math.random() * (this.s-x));
        while(p1==p2){
            p2 = Math.round(Math.random() * (this.s-x));
        }
        r.push([p1, p2]);
    }
    return r;
};

genetic.prototype.operator = function(a, b){

    var c = Math.floor(Math.random() * this.g);

    var x = a.slice(0, c) + b.slice(c, a.length);
    var z = b.slice(0, c) + a.slice(c, a.length);

    return [x, z];
};

var example = new genetic({
    size: 100,
    elimination: 0.4,
    mutation: 0.01,
    geneSize: 20
});