/warehouse-path

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

Primary LanguageJavaScript

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