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.

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

The fitness (objective value) through iterations.

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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/