Abstract: Travelling Salesman Problem (TSP) is one of the best known NP-hard problems. It is also a classic tour problem in which a hypothetical salesman must find the most efficient sequence of destinations in his territory, stopping only once at each, and ending up at the initial starting location. To handle with this problem there is no suitable algorithm that solves it in polynomial time. Many algorithms were applied to solve TSP with more or less success. There are many ways to classify algorithms, each with its own merits. This paper is a review on various algorithms like Ant Colony Optimization Algorithms (ACO), Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) available with respective attributes to find the nearest optimal solution for the traveling salesman problem. It also relates the traveling salesman problem with the available algorithms and provides the advantages in providing a solution for TSP.