Traveling Salesman Implementation in Ruby

Description

Implementation of the Traveling Salesmen Problem in ruby.

The Traveling Salesman Problem attempts to create an optimal tour from a starting Location through all other Locations in the graph and back to the start. The problem is NP-Complete so hueristics will be used to attempt to optimize an initial Tour.

Heuristics Used

Allows the use of two heuristics for optimizing Tours:

Genetic Algorithm
Two-Opt

The Genetic Algorithm will evolve a population of the specified number of generations. This is done by a process called crossover, as well as, random mutation in a Tour. Crossover takes two of the fittest Tours of a sample of the population and crosses them to create an offspring. Mutation will randomly swap locations in a tour at a specified rate (default 1.5%)

I wrote the genetic algorithm because I thought it would be fun, but it is not very deterministic. I also implemented a Two-Opt approach. Two-Opt seeks to untangle places where the tour crosses over itself, as in the following diagram:

      - A   B -               - A - D -
          X         ==>       
      - C   D -               - C - B -

The algorithm works by finding the two indices (i, j) where a crossover exits and:

Copying the indices from 0 to i - 1 forwards into another Tour
Copying the indices from i to j in reverse into the new Tour
Copying the indices from j+1 to the end forwards into the new Tour

Imagine you are taking a loop of string that has been twisted and twisting it back.

Two-Opt Search is basically a trial and error approach where you test every combination of i and j and keep the resultant Tour if it is better than the previous.

Seed Algorithms

Two seed algorithms have been included for testing the capabilities of the two algorithms.

Nearest Neighbor
Random Tour

The Nearest Neighbor starts at a random point and builds a path by finding its nearest neighbor. It repeats this process from each subsequent nearest neighbor until the Tour is complete

The Random Tour algorithm just creats a random ordering of locations.

File Input

Locations are passed to the program by file. The format of the file should be as follows:

0 x y
1 x y
3 x y
...
n-1 x y
n x y

Usage

Usage: ruby tsp_main.rb [options]

Mandatory options:
    -f, --infile=FILE                Specify the Input File
    -p, --population-size=SIZE       Set the population size
    -g, --generations=NUMBER         Set the number of generations

Special Options:
        --algo=[TYPE]                Select algorithm type (genetic (default), two_opt)
        --seed-algo=[TYPE]           Select seed algorithm type (nearest_neighbor (default), random_tour)
    -c, --crossover=SIZE             Set the size of crossover sample
population (default: 20)
    -r, --mutation-rate=FLOAT        Set the mutation rate ( range: 0.0-0.25,
default: 0.015)

Informational options:
    -h, --help                       Display Help Message
        --version                    Show version

wteuber / tsp-ruby