Traveling Salesman Problem
The Traveling Salesman Problem (TSP) is a classic algorithmic problem in computer science and operations research that focuses on optimization. It involves finding the shortest possible route that visits a given set of cities exactly once and returns to the origin city, making it a fundamental example of an NP-hard combinatorial optimization problem. TSP is widely used to model real-world scenarios in logistics, manufacturing, and network design.
Developers should learn TSP to understand key concepts in algorithm design, optimization, and computational complexity, which are essential for solving routing, scheduling, and resource allocation problems in applications like delivery services, circuit board drilling, and DNA sequencing. It provides a foundation for studying heuristic and approximation algorithms, such as genetic algorithms or simulated annealing, when exact solutions are computationally infeasible for large datasets.