TSP (Traveling Salesman Problem) - Implementation Approaches using MATLAB and LINGO

In this documentation, we explore the Traveling Salesman Problem (TSP) and its solution approaches using different optimization algorithms. The implementation includes MATLAB-based Genetic Algorithm (GA) that evolves population solutions through selection, crossover and mutation operations, MATLAB-based Simulated Annealing (SA) that uses probabilistic acceptance of worse solutions to escape local optima, and LINGO-based Dynamic Programming that breaks down the problem into overlapping subproblems for optimal path calculation. These algorithms help identify optimal travel routes to minimize total distance by iteratively improving solution quality through different optimization mechanisms. By applying these algorithmic approaches to TSP, we can obtain improved solutions and contribute to both research and practical applications of the traveling salesman problem. The MATLAB implementations typically involve defining fitness functions for route evaluation, while LINGO models use mathematical programming formulations for exact solutions.