Travelling Salesman Problem: An Empirical Comparison Between ACO, PSO, ABC, FA and GA

Abstract

Travelling salesman problem (TSP) is one of the optimization problems which has been studied with a large number of heuristic and metaheuristic algorithms, wherein swarm and evolutionary algorithms have provided effective solutions to TSP even with a large number of cities. In this paper, our objective is to solve some of the benchmark TSPs using ant colony optimization (ACO), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA) and genetic algorithm (GA). The empirical comparisons of the experimental outcomes show that ACO and GA outperform to ABC, PSO and FA for the given TSP.