TSP Algorithm Implementation Using Simulated Annealing Optimization

Based on my experience, I suggest further enhancing the code documentation. We should include detailed comments explaining the operational logic at each step and the rationale behind implementation choices. This approach would make the code accessible even to those unfamiliar with simulated annealing algorithms. The code implements key components including temperature scheduling, neighbor solution generation through city swaps, and energy (cost) calculation using Euclidean distances. I recommend conducting additional test cases with varying city configurations and parameter settings (cooling rate, initial temperature) to ensure robustness across different scenarios. This would increase confidence in deployment. Furthermore, we could improve code maintainability by adding function headers describing input/output parameters and incorporating error handling for invalid inputs. Ultimately, investing in code readability and reliability through structured comments and comprehensive testing will significantly enhance the user experience.