Aims to find a complete route that connects all the nodes of a network, visiting them only once and returning to the starting point.
Published in Chapter:
Comparative Analysis of ACO Algorithms for the Solution of the Travelling Salesman Problem
Gloria Lola Quispe (Facultad de Ingeniería, Universidad Nacional de Jujuy, Argentina), Maria Fernanda Rodríguez (Facultad de Ciencias Económicas, Argentina), and José Daniel Ontiveros (Facultad de Ingeniería, Universidad Nacional de Jujuy, Argentina)
Copyright: © 2021
|Pages: 21
DOI: 10.4018/978-1-7998-7010-4.ch014
Abstract
Metaheuristics are non-deterministic algorithms. Metaheuristic strategies are related to design. This chapter presents an introduction on metaheuristics, from the point of view of its theoretical study and the foundations for its use. Likewise, a description and comparative study of the ant colony-based algorithms is carried out. These are ant system (AS), ant colony system (ACS), and max-min ant system (MMAS). These results serve to deliver solutions to complex problems and generally with a high degree of combinatorics for those there is no way to find the best reasonable time. An experimentation and analysis of the results of the ACO algorithms (optimization by ants colonies) is also carried out. For the evaluation of the algorithms, comparisons are made for instances of the TSPLIB test instance library. Therefore, it is deepened in the resolution of the travelling salesman problem (TSP), and a comparative analysis of the different algorithms is carried out in order to see which one adjusts better.