CISUC

MC-ANT: a Multi-colony Ant Algorithm

Authors

Abstract

In this paper we propose an ant colony optimization variant where several independent colonies try to simultaneously solve the same problem. The approach includes a migration mechanism that ensures the exchange of information between colonies and a mutation operator that aims to adjust the parameter settings during the optimization.
The proposed method was applied to several benchmark instances of the node placement problem. The results obtained shown that the multi-colony approach is more effective than the single-colony. A detailed analysis of the algorithm behavior also reveals that it is able to delay the premature convergence.

Keywords

Ant Colony Optimization, Multiple colony, Node Place- ment Problem, Bidirectional Manhattan Street Network

Subject

Evolutionary Optimization

Conference

Artificial Evolution (EA '09), October 2009

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DOI


Cited by

Year 2019 : 2 citations

 Bouzbita S., El Afia A., Faizi R. (2019) Hidden Markov Model Classifier for the Adaptive ACS-TSP Pheromone Parameters. In: Talbi EG., Nakib A. (eds) Bioinspired Heuristics for Optimization. Studies in Computational Intelligence, vol 774. Springer, Cham

 Abdelbar, A. M., Salama, K. M. (2019) Parameter Self-Adaptation in an Ant Colony Algorithm for Continuous Optimization. In: IEEE Access, vol. 7, pp. 18464-18479.
doi: 10.1109/ACCESS.2019.2896104

Year 2018 : 1 citations

 Bouzbita, S., El Afia, A., Faizi, R. Parameter Adaptation for Ant Colony System Algorithm using Hidden Markov Model for TSP Problems, Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications, {LOPAL}, ACM, 2018, doi:10.1145/3230905.3230962

Year 2017 : 1 citations

 Bouzbita, S., El Afia, A., Faizi, R., "A novel based Hidden Markov Model approach for controlling the ACS-TSP evaporation parameter", In: Proceedings of 2016 5th International Conference on Multimedia Computing and Systems, ICMCS 2016, pp. 633-638, April 2017, ISBN: 9781509051465, DOI: https://doi.org/10.1109/ICMCS.2016.7905544

Year 2016 : 1 citations

 Kengo Katayama , Yusuke Okamoto, Elis Kulla, Noritaka Nishihara, "Variable Neighborhood Search Algorithms for the Node Placement Problem in Multihop Networks", Advances on Broad-Band Wireless Computing, Communication and Applications, LNCS, 2, pp. 631-638, October 2016

Year 2015 : 1 citations

 Rafid Sagban, Ku Ruhana KuMahamud and Muhamad Shahbani Abu Bakar, Nature-inspired Parameter Controllers for ACO-based Reactive Search, Research Journal of Applied Sciences, Engineering and Technology 10(1): 109117, 2015

Year 2014 : 1 citations

 K. Katayama, Y. Akagi, E. Kulla, H. Minamihara, and N. Nishihara, “New Kick Operators in Iterated Local Search Based Metaheuristic for Solving the Node Placement Problem in Multihop Networks,” in 2014 17th International Conference on Network-Based Information Systems, 2014, pp. 141–148.

Year 2013 : 2 citations

 Ana Maria A.C. Rocha, M. Fernanda P. Costa, Edite M.G.P. Fernandes, Distribution based artificial fish swarm in continuous global optimization, Atas do XVI Congresso da Associação Portuguesa de Investigação Operacional, Oliveira, José F.; Vaz, Clara B. (Eds.), Instituto Politécnico de Bragança, p. 306-312, 2013.

 LIU Rui-jie, WANG Li-juan, SHI Yuan. Multi-Colony Ant Algorithm Applied to the Rectangular Pieces Layout Optimization. Journal of Jiangnan University(Natural Science Edition). 2013, 12(3)

Year 2012 : 1 citations

 P Deepalakshmi, S Radhakrishnan. Online parameter tuning using Particle Swarm Optimization for ant-based QoS routing in mobile ad-hoc networks. International Journal of Hybrid Intelligent Systems, IOS Press, 2012.

Year 2011 : 1 citations

 Stützle, T., López-Ibánez, M., Pellegrini, P., Maur, M., De Oca, M. M., Birattari, M., & Dorigo, M. (2011). Parameter adaptation in ant colony optimization. In Autonomous search (pp. 191-215). Springer Berlin Heidelberg.

Year 2010 : 2 citations

 Gómez Díaz, Yudel Rodrigo, Algoritmos que combinan conjuntos aproximados y optimización basada en colonias de hormigas para la selección de rasgos. Extensión a múltiples fuentes de datos, PhD Thesis, Universidad Central “Marta Abreu” de Las Villas. Facultad de Matemática, Física y Computación. Departamento Ciencias de la Computación, 2010

 Thomas Stutzle, Manuel Lopez-Ibanez, Paola Pellegrini, Michael Maur, Marco Montes de Oca, Mauro Birattari, and Marco Dorigo, Parameter Adaptation in Ant Colony Optimization, IRIDIA " Technical Report Series, Technical Report No. TR/IRIDIA/2010-002, January 2010