Abstract
Traveling Salesman problem is the most recognized NP-hard problem for the researches in the field of computer science which focused on optimization. TSP finds the minimum travelling distance between given set of cities by traversing each of these cities only once except the starting city. This study discusses the salesman problem by presenting Particle Swarm Optimization Algorithm (PSO), Ant Colony Optimization algorithm (ACO) and Genetic Algorithm (GA) which intends to solve the problem. In this paper, these algorithms are applied on the benchmark TSP dataset Oliver 30. Also, the paper provides comparison between these algorithms and this comparison helps to choose the better algorithm.
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