npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

warehouse-path

v1.0.0

Published

Lib allowing you to compare routing algorithm performance for warehouse picker tour.

Downloads

3

Readme

warehouse-path

Lib that allow you to build to best picket tour inside a warehouse for a given list of locations to visit. Inside a warehouse a picker must pick during his/her tour 40 to 60 products, those products are located across many locations, warehouse-path allow you to define the best way to go throught all locations and minimize the length of the tour.

Installation

npm i --save warehouse-path

Usage

const R = require('ramda');

const {
  nbSteps,
  shortestClosestNeighbourPath,
  shortestPathViaEllipse,
  shortestSShapedPath,
  warehouseMatrix,
} = require('../index');

///////////////////////////////////
// Create your warehouse matrix //
/////////////////////////////////

const matrix = warehouseMatrix(44, 36, [10]);

/////////////////////////////////////////////////
// Define your picker tour via your locations //
///////////////////////////////////////////////

const pickerTour = ['MZ1-0115A03', 'MZ1-0122A01', 'MZ1-0332A03', 'MZ1-2531A03', 'MZ1-2813D05', 'MZ1-2816D04', 'MZ1-2913D05', 'MZ1-3019D01', 'MZ1-3334A02', 'MZ1-3341A02', 'MZ1-3517A03', 'MZ1-3529A01', 'MZ1-3227A02', 'MZ1-0715A01'];

///////////////////////////////////////////////
// Define your starting and/or ending point //
/////////////////////////////////////////////

const sortingArea = 'MZ1-2444A01';

/////////////////////////////////////////////////////////////////////////////////////
// Define your custom function to transform your locations into matrix data point //
///////////////////////////////////////////////////////////////////////////////////

// testLocationToMatrixData :: String -> [Number, Number]
function testLocationToMatrixData(location) {
  const val = R.slice(4, 11, location);
  const xAxis = R.subtract(R.multiply(Number(R.slice(0, 2, val)), 3), 3);
  const yAxis = Number(R.slice(2, 4, val));

  if (R.equals(0, R.modulo(yAxis, 2))) {
    return [R.inc(xAxis), R.divide(yAxis, 2)];
  } else {
    return [xAxis, R.divide(R.inc(yAxis), 2)];
  }
}


console.log('S Shaped', nbSteps(shortestSShapedPath(matrix, sortingArea, pickerTour, testLocationToMatrixData)));
console.log('Closest Neighbour', nbSteps(shortestClosestNeighbourPath(matrix, sortingArea, pickerTour, testLocationToMatrixData)));
console.log('Ellipse', nbSteps(shortestPathViaEllipse(matrix, sortingArea, pickerTour, testLocationToMatrixData)));

Will output via the node terminal node example/example-1.js

S Shaped 397
Closest Neighbour 382
Ellipse 347

Those numbers means that each algo will ask the picker to go throught that many steps to complete their picker tour. In the example above the ellipse algo is the best for this given picker tour.

Performance between S-Shaped and closest neighbour algos

alt text

  • S-Shape = S-Shaped
  • Shortest = closest neighbour
  • Difference = closest neighbour steps for a given picker tour minus S-Shaped steps for a given picker tour

The closest neighbour tends to performance better than the S-Shaped and this is even more true as the number of locations in a picker tour increase.

Performance between S-Shaped and ellipse algos

alt text

  • S-Shape = S-Shaped
  • Ellipse = ellipse
  • Difference = ellipse steps for a given picker tour minus S-Shaped steps for a given picker tour

The ellipse tends to performance better than the S-Shaped and this is even more true as the number of locations in a picker tour increase. It also outperform the closest neighbour algo.

Reading list and useful websites

  • https://simple.wikipedia.org/wiki/Travelling_salesman_problem
  • https://simple.wikipedia.org/wiki/Monte_Carlo_algorithm
  • https://simple.wikipedia.org/wiki/Las_Vegas_algorithm
  • https://en.wikipedia.org/wiki/Branch_and_bound
  • https://m3ideas.org/2014/09/26/walking-directions-in-a-warehouse-part-2/
  • http://will.thimbleby.net/a-shortest-path-in-javascript/
  • http://theory.stanford.edu/~amitp/GameProgramming/
  • https://en.wikipedia.org/wiki/Artificial_ants
  • http://www.cse.yorku.ca/~aaw/Zambito/TSP_Euclidean_PTAS.pdf
  • https://en.wikipedia.org/wiki/Euclidean_distance
  • http://gbb.mehr-davon.de/
  • http://gbb.mehr-davon.de/content/median-circle-problem/example.html
  • http://mathworld.wolfram.com/Ellipse.html
  • https://developers.google.com/optimization/routing/tsp/tsp