An improved discrete bat algorithm for symmetric and asymmetric Traveling Salesman Problems

Bat algorithm is a population metaheuristic proposed in 2010 which is based on the echolocation or bio-sonar characteristics of microbats. Since its first implementation, the bat algorithm has been used in a wide range of fields. In this paper, we present a discrete version of the bat algorithm to solve the well-known symmetric and asymmetric traveling salesman problems. In addition, we propose an improvement in the basic structure of the classic bat algorithm. To prove that our proposal is a promising approximation method, we have compared its performance in 37 instances with the results obtained by five different techniques: evolutionary simulated annealing, genetic algorithm, an island based distributed genetic algorithm, a discrete firefly algorithm and an imperialist competitive algorithm. In order to obtain fair and rigorous comparisons, we have conducted three different statistical tests along the paper: the Student’s t-test, the Holm’s test, and the Friedman test. W...

• Type: Journal
• Year: 2016
• Where: EAAI
• Authors: Eneko Osaba, Xin-She Yang, Fernando Díaz, Pedro López-García, Roberto Carballedo
• Keywords: EAAI 2016, Emerging Technology