👉 Traveling salesman problems (TSP) involve finding the shortest possible route that visits each city exactly once and returns to the starting point. The "traveling math" refers to the mathematical techniques and algorithms developed to tackle this optimization problem, which is NP-hard, meaning it becomes computationally infeasible to solve exactly for large numbers of cities with brute-force methods. Instead, heuristic and approximation algorithms are used to find near-optimal solutions efficiently. These methods include genetic algorithms, simulated annealing, and ant colony optimization, each inspired by natural processes to explore the vast solution space and find practical routes that minimize travel distance or time.
