https://github.com/s-soltys/genetic-optimization

A simple genetic optimization library for TypeScript.
https://github.com/s-soltys/genetic-optimization

Last synced: about 2 months ago
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A simple genetic optimization library for TypeScript.

• Host: GitHub
• URL: https://github.com/s-soltys/genetic-optimization
• Owner: s-soltys
• License: mit
• Created: 2017-03-29T12:31:42.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-03-30T08:23:56.000Z (over 7 years ago)
• Last Synced: 2024-10-04T01:35:14.415Z (3 months ago)
• Language: TypeScript
• Size: 7.81 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Genetic optimization

[![Build Status](https://travis-ci.org/s-soltys/genetic-optimization.svg?branch=master)](https://travis-ci.org/s-soltys/genetic-optimization)

A simple library used to find an optimal solution to a problem.

### How to install

```

npm install --save genetic-optimization

```

### How to use

Example implementation of a simple exponential math function:

```typescript

import { Optimizer } from "genetic-optimization";

// the optimized exponential function

let expFn = (x: number) => -Math.pow(x - expectedSolution, 2);

let expectedSolution = 25;

// construct the optimizer

let optimizer = new Optimizer({

    evaluate: expFn,

    crossover: (a, b) => (a+b)/2 + (Math.random()-0.5)/4,

    endCondition: (input, score, generation) => generation === 10

});

// generate initial population

let population = new Array(5000);

for (let i = 0; i < population.length; i++){

    population[i] = (Math.random() - 0.5) * 100;

}

// run the optimization algorithm

let foundSolution = optimizer.findOptimal(population);

// assert solution

expect(foundSolution).toBeCloseTo(expectedSolution, 1);

```