/simulated-annealing-tsp

Simulated Annealing algorithm to solve Travelling Salesmen Problem in Python

Primary LanguagePythonMIT LicenseMIT

Simulated Annealing algorithm to solve Travelling Salesman Problem in Python

Using simulated annealing metaheuristic to solve the travelling salesman problem, and visualizing the results.

Starts by using a greedy algorithm (nearest neighbour) to build an initial solution.

A simple implementation which provides decent results.


An example of the resulting route on a TSP with 100 nodes.

Route Graph

The fitness (objective value) through iterations.

Learning Plot


References Kirkpatrick et al. 1983: "Optimization by Simulated Annealing"

http://www.blog.pyoung.net/2013/07/26/visualizing-the-traveling-salesman-problem-using-matplotlib-in-python/