/tsp

traveling salesman optimization using simulated annealing

Primary LanguagePython

Optimization of the Traveling Salesman Problem

This is a command line program that generates a randomized traveling salesman problem of a given size and attempts to optimize a solution using simulated annealing.

Help

Use the -h or --help switch to view help text in your terminal.

  • -s or --size determines the size of the problem, i.e. the number of cities to travel. The default is 20.
  • -a or --sa is a switch to use the simulated annealing method. It defaults to true.
  • -m or --mcmc is a switch to use the markov chain monte carlo method. It defaults to false.
  • -r or --report is a switch to turn on code performance reporting using the cProfile python library.
  • -i or --iterations determines the number of iterations to run at each temperature.
  • -o or --output is a switch to turn on result output, saving data and graphs. It defaults to off.