The Traveling Salesperson Problem (TSP) is a famous optimization problem with applications in logistics, manufacturing, and art. In its planar form, we are given a set of "cities", and we want to visit each city while minimizing the total travel distance.

Finding the shortest possible tour is NP-hard, and quickly becomes infeasible as the number of cities grows. But most applications need only a heuristically good solution: a tour which is short, if not the shortest possible. The Lin-Kernighan heuristic quickly produces such tours.

The Concorde project provides a well-regarded collection of TSP solvers. I needed TSP heuristics for a Haskell project, so I wrote a Haskell interface to Concorde's Lin-Kernighan implementation. Concorde provides a C library, but it's far from clear how to use it. Instead I chose to invoke the `linkern`

executable as a subprocess.

The core of the Haskell interface looks like this:

`tsp`

:: Config -- provides various configurable parameters

-> (a -> R2) -- gives the rectangular coordinates of each point

-> [a] -- list of points to visit

-> IO [a] -- produces points permuted in tour order

`tsp`

lets you represent the points to visit using any type you like. You just provide a function to get the coordinates of each point. The `Config`

parameter controls various aspects of the computation, including the time/quality tradeoff. Defaults are provided, and you can override these selectively using record-update syntax. All considered it's a pretty simple interface which tries to hide the complexity of interacting with an external program.

# Visualizing a tour

Here's a example program which computes a tour of 1,000 random points. We'll visualize the tour using the Diagrams library.

`import Diagrams.Prelude`

( Diagram , Point(P), fillColor , lineWidth

, translate, circle , fromVertices, lightgrey )

import Diagrams.Backend.Cairo.CmdLine

( Cairo, defaultMain )

import Data.Colour.SRGB ( sRGB )

import Data.Colour.RGBSpace ( uncurryRGB )

import Data.Colour.RGBSpace.HSV ( hsv )

import qualified Algorithms.Concorde.LinKern as T

import Control.Monad

import Data.Monoid

import System.Random

`tsp`

takes a list of points and a function to extract the coordinates of a point. Our points are just the coordinates themselves, so we pass the identity function.

`type R2 = (Double, Double)`

findTour :: [R2] -> IO [R2]

findTour = T.tsp cfg id where

cfg = T.defConfig { T.verbose = True }

The tour is drawn as a loop of line segements. We also shade the interior of this polygon.

`diaTour :: [R2] -> Diagram Cairo R2`

diaTour xs@(x:_) = sty . fromVertices $ map P (xs ++ [x]) where

sty = fillColor lightgrey . lineWidth 10

Each point visited by the tour is drawn as a circle, with hue indicating its position in the tour.

`diaPoints :: [R2] -> Diagram Cairo R2`

diaPoints = mconcat . map circ . zip [0..] where

n = fromIntegral numPoints

circ (i,p) = translate p . fillColor color $ circle 40

where color = uncurryRGB sRGB (hsv (360*i/n) 1 1)

Now we put it all together. Note that `linkern`

uses Euclidean distances rounded to the nearest integer. So we need coordinates with fairly large magnitudes. Picking values between 0 and 1 won't work.

`numPoints :: Int`

numPoints = 1000

main :: IO ()

main = do

let rnd = randomRIO (0,10000)

points <- replicateM numPoints (liftM2 (,) rnd rnd)

tour <- findTour points

defaultMain (diaPoints tour `mappend` diaTour tour)

We run it like so:

```
$ export PATH=~/concorde-031219/LINKERN:$PATH
$ runhaskell tour.lhs -o out.pdf
$ xpdf out.pdf
```

The computation takes about 2 seconds on my machine. And the output looks like this:

You can download this post as a Literate Haskell file and run the above program. You'll need to install the `concorde`

and `diagrams`

packages.

The source for the `concorde`

Haskell package includes a more full-featured version of this example.

Nice article, thanks for the information. It's very complete information. I will bookmark for next reference

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