genetic-algorithm

Foundation of algorithms and patterns taken and modified from here:
http://burakkanber.com/blog/machine-learning-genetic-algorithms-in-javascript-part-2/#fiddle

But code has all been rewritten.

Usage

This example solves the same knapsack problem that Burak Kanber has walked through in the above link.

``
const { Chromosome, Population } = require('genetic-algorithm-js');

class KnapsackChromosome extends Chromosome {

mutateGenes(genes) {
const doMutation = Math.random() <= MUTATION_RATE;

if (doMutation) {
const pivot = utilities.getRandomInt(0, genes.length);
const mutatedValue = utilities.toNumber(!!!utilities.toNumber(genes.slice(pivot, pivot + 1)));
return genes.slice(0, pivot) + mutatedValue + genes.slice(pivot + 1);
}
else {
return genes;
}
}

createGenes() {
return _.join(
_.map(
_.range( 0, _.size(blueprint) ),
() => Math.round(Math.random())
),
''
);
}

calculateFitness() {
const genes = this.getGenes();

const penalty = 50;
const maxWeight = 1000;

const { value: reducedValue, weight: reducedWeight } = _.reduce(
genes.split(''),
(agg, val, idx) => {
if (utilities.toNumber(val)) {

const dataAtIndex = (
(SORTED_BLUEPRINT_LOOKUP || [])[idx]
) || {};

const additionalWeight = utilities.toNumber(dataAtIndex['weight'])
const additionalValue = utilities.toNumber(dataAtIndex['value']);

agg.weight += additionalWeight;
agg.value += additionalValue;

return agg;

}
else {
return agg;
}
},
{
value: 0,
weight: 0
}
);

const penaltyToDeduct = Math.max(reducedWeight - maxWeight, 0) * penalty;

return reducedValue - penaltyToDeduct;
}

mate(partner) {
return _.map(
utilities.doStringMate(this.getGenes(), partner.getGenes()),
genes => new KnapsackChromosome({genes})
)
}
}

class KnapsackPopulation extends Population {
createChromosome() {
return new KnapsackChromosome();
}
};

new KnapsackPopulation({
maximumSize: SIZE_OF_POPULATION,
})
.age(AGE)
.getMembers()

``