Abstract
Ant Colony Optimization (ACO) has been used to solve several optimization problems. However, in this paper, the variants of ACO have been applied to solve the Traveling Salesman Problem (TSP), which is used to evaluate the variants ACO as Benchmark problems. Also, we developed a graphical interface to allow the user input parameters and having as objective to reduce processing time through a parallel implementation. We are using ACO because for TSP is easily applied and understandable. In this paper we used the following variants of ACO: Max-Min Ant System (MMAS) and Ant Colony System (ACS).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Almirón, M., Barán, B., Chaparro, E.: Ant Distributed System for Solving the Traveling Salesman Problem. In: XXV lnformatic Latinoamerican Conf.-CLEI, Paraguay, pp. 779–789 (1999)
Barán, B., Sosa, R.: A New approach for AntNet routing. In: IEEE Ninth International Conference onComputer Commnunications and Networks, Las Vegas, Nevada (2000)
de la Cruz, J., Mendoza, A., del Castillo, A., Paternina, C.: Comparative Analysis of heuristic Approaches Ant Q, Simulated Annealing and Tabu Search in Solving the Traveling Salesman. Departamento de Ciencias de la Computación e Inteligencia Artificial, E.T.S. Ingenieria Informática, Granada, España (2003)
Dorigo, M., Stutzle, T.: Ant Colony Optimization. Massachusetts Institute of Technology, MIT Press, Bradford, Cambridge (2004)
Favaretto, D., Moretti, E., Pellegrini, P.: Ant colony system for variants of traveling salesman problem with time windows, Technical Report. Applied Mathematics Department of Ca’ Foscari University of Venice, No. 120/2004 (2004)
Cordón, O., Moya, F., Zarco, C.: A new evolutionary algorithm combining simulated annealing and genetic programming for relevance feedback in fuzzy information retrieval systems. Soft Computing 6(5), 308–319 (2002)
Pavez, A., Acevedo, H.: An Algorithm ACS Motion Prompt and Operator 2-Opt, Departamento de Informatica. Universidad Técnica Federico Santa Maria (2002)
Website of Ant Colony Optimization Algorithms official, http://www.aco-metaheuristic.org (accessed May 5, 2012)
Website of interface design, http://www.matpic.com , MC. Diego O. Barragán Guerrero, Universidad Estatal de Campinas, Brasil, www.unicamp.br (accessed May 2012)
Website of Matlab, http://www.mathworks.com (accessed May 2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Chaparro, I., Valdez, F. (2013). Variants of Ant Colony Optimization: A Metaheuristic for Solving the Traveling Salesman Problem. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Recent Advances on Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33021-6_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-33021-6_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33020-9
Online ISBN: 978-3-642-33021-6
eBook Packages: EngineeringEngineering (R0)