用 Python 解决旅行商问题的 模拟退火算法_python_代码_下载

Simulated Annealing algorithm to solve Travelling Salesman Problem in Python =================== Using [simulated annealing](https://en.wikipedia.org/wiki/Simulated_annealing) metaheuristic to solve the [travelling salesman problem](https://en.wikipedia.org/wiki/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.  The fitness (objective value) through iterations.  ---------- **References** [Kirkpatrick et al. 1983: "Optimization by Simulated Annealing"](http://www2.stat.duke.edu/~scs/Courses/Stat376/Papers/TemperAnneal/KirkpatrickAnnealScience1983.pdf) http://www.blog.pyoung.net/2013/07/26/visualizing-the-traveling-salesman-problem-using-matplotlib-in-python/