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 = ; const nbSteps shortestClosestNeighbourPath shortestPathViaEllipse shortestSShapedPath warehouseMatrix = ; ///////////////////////////////////// Create your warehouse matrix /////////////////////////////////// const matrix = ; /////////////////////////////////////////////////// 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] { const val = R; const xAxis = R; const yAxis = NumberR; if R return R R; else return xAxis R; } console;console;console;
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.
S-Shaped
and closest neighbour
algos
Performance between - S-Shape =
S-Shaped
- Shortest =
closest neighbour
- Difference =
closest neighbour
steps for a given picker tour minusS-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.
S-Shaped
and ellipse
algos
Performance between - S-Shape =
S-Shaped
- Ellipse =
ellipse
- Difference =
ellipse
steps for a given picker tour minusS-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