Created
January 11, 2016 07:48
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Simple but powerful Genetic Algorithm
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/** | |
* 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 | |
}); |
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