Solving Traveling Salesman Problem (TSP) Using Simulated Annealing Algorithm (SA)

This project presents a MATLAB-based program utilizing the Simulated Annealing (SA) algorithm to solve the Traveling Salesman Problem (TSP). TSP is a classic combinatorial optimization problem aiming to find the shortest possible route enabling a salesman to visit all given cities exactly once and return to the origin city. The SA algorithm mimics the physical process of metal annealing, employing probabilistic acceptance criteria to escape local optima and gradually converge toward global solutions. The MATLAB implementation incorporates key components including: - Distance matrix calculation for inter-city distances - Temperature scheduling with exponential cooling - Metropolis criterion for solution acceptance - 2-opt or inversion-based neighborhood generation Through adjustable parameters like initial temperature, cooling rate, and Markov chain length, users can obtain diverse solutions and compare their performance. The program provides researchers and students with a practical tool for studying TSP optimization techniques, while offering reference value for real-world path planning applications. The code structure allows straightforward modification of objective functions and neighborhood operators for algorithm customization.