Traveling salesman problem (tsp) using simulated annealing

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Traveling salesman problem (tsp) using simulated annealing

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In the given document, we discuss the application of the simulated annealing algorithm to solve the well-known optimization problem known as the Traveling Salesman Problem (TSP). The TSP is a classic problem in computer science and mathematics, which involves finding the shortest possible route that a salesman can take to visit a given set of cities and return to the starting point. By applying the simulated annealing technique, we aim to find an optimal or near-optimal solution to this problem. Simulated annealing is a metaheuristic algorithm inspired by the annealing process in metallurgy, which gradually cools a material to reduce its defects and improve its overall structure. Similarly, in the context of the TSP, simulated annealing iteratively searches for better solutions by allowing temporary increases in the objective function, enabling exploration of the solution space and avoiding getting trapped in local optima. Thus, by utilizing simulated annealing, we can tackle the TSP and find improved solutions that can be of great value in various real-world applications.