Simple but Powerful Simulated Annealing NPM Library (with Demo)

Simulated Annealing is a general-purpose meta heuristic optimization algorithm. It is similar to hill climbing but SA has the ability to jump out of local optimal with a decreasing probability.

local-global-minimum

We can think of SA as the following scenario: A drunk rabbit jumps randomly as she wants to reach the hill top. As she wakes up gradually little by little, she walks steady to the hill top…

I have created a easy (simple to use) and yet very powerful tiny framework to adopt the SA to general math optimisation problems.

Technology Stack

Latest Javascript (ECMAScript 2016) and wrapped in NPM Library:

Project Page

NPM: https://www.npmjs.com/package/simulated_annealling

Unit Test

Unit tests are built upon mocha and chai unit testing framework. And you can run test via npm test

npm-test-mocha

Simulated Annealing Demo in Javascript

The following will use the SA library to search the answer(s) for equation $tex_f2a605137e5420286592feab72726237 Simple but Powerful Simulated Annealing NPM Library (with Demo) algorithms github javascript math$

var SimulatedAnnealing = require('simulated_annealling').SimulatedAnnealing;
 
var GetAnswerOfXSquareEqualsSixteen = (function() {
    // parameters
    let options = {
        coolingFactor: 0.09,
        stabilizingFactor: 1.005,
        freezingTemperature: 0.001,
        initialTemperature: 15,
        initialStabilizer: 30
    }
 
    // final solution 
    let x;
    // current solution
    let cur;
 
    const getCost = (v) => {
        return Math.abs(v * v - 16);
    }
 
    const generateNeighbor = () => {
        // neighbour is within 0.5 distance
        cur = x + (Math.random() - 0.5);
        return getCost(cur);
    }
 
    const generateNewSolution = () => {
        cur = Math.random() * 16; // guess a number between 0 to 16
        x = cur;
        return getCost(cur);
    }
 
    const acceptNeighbor = () => {
        x = cur;
    }   
 
    // pass parameters to SA object
    let SA = SimulatedAnnealing(options, generateNewSolution, generateNeighbor, acceptNeighbor);
 
    // we need to continue simulating if temperature is still high
    while (SA.Do()) {
        // console.log("Temperature: " + SA.GetCurrentTemperature());
        // console.log("GetCurrentEnergy: " + SA.GetCurrentEnergy());
    }
 
    // final solution
    console.log("Solution is: " + x);
})()

var SimulatedAnnealing = require('simulated_annealling').SimulatedAnnealing;

var GetAnswerOfXSquareEqualsSixteen = (function() {
    // parameters
    let options = {
        coolingFactor: 0.09,
        stabilizingFactor: 1.005,
        freezingTemperature: 0.001,
        initialTemperature: 15,
        initialStabilizer: 30
    }

    // final solution 
    let x;
    // current solution
    let cur;

    const getCost = (v) => {
        return Math.abs(v * v - 16);
    }

    const generateNeighbor = () => {
        // neighbour is within 0.5 distance
        cur = x + (Math.random() - 0.5);
        return getCost(cur);
    }

    const generateNewSolution = () => {
        cur = Math.random() * 16; // guess a number between 0 to 16
        x = cur;
        return getCost(cur);
    }

    const acceptNeighbor = () => {
        x = cur;
    }   

    // pass parameters to SA object
    let SA = SimulatedAnnealing(options, generateNewSolution, generateNeighbor, acceptNeighbor);

    // we need to continue simulating if temperature is still high
    while (SA.Do()) {
        // console.log("Temperature: " + SA.GetCurrentTemperature());
        // console.log("GetCurrentEnergy: " + SA.GetCurrentEnergy());
    }

    // final solution
    console.log("Solution is: " + x);
})()

This example is also used as a unit test case.

Github: https://github.com/DoctorLai/simulated_annealling

–EOF (The Ultimate Computing & Technology Blog) —

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